Investigating the Effects of Age on Senior Citizens During Hands-Free Mobile Phone Activity

Conference paper

Ossai, B., Sharif, S. and Fu, C. 2024. Investigating the Effects of Age on Senior Citizens During Hands-Free Mobile Phone Activity. 2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies.
AuthorsOssai, B., Sharif, S. and Fu, C.
TypeConference paper
Abstract

Driving and utilizing a mobile phone becomes legitimate only if it is in hands-free mode. Nonetheless, due to the driver's deflected concentration to the phone and the driving task, utilizing a mobile phone hands-free result in cognitive distraction. Based on the blood pressure (BP) of drivers, this investigation determined real-time age effects of talking on mobile phones hands-free during driving. The cognitive implication was assessed through drivers’ BP. During driving and parking in the bay in reverse, the subjects performed two number-related tasks of increasing level of difficulty. The findings indicate that participant's BP during phone conditions increased and surpassed their BP under no-phone conditions. According to qualitative results, the task accomplishment had a profound cognitive effect on the subjects. The qualitative questionnaire yielded empirical proof of the drivers' cognitive abilities, corroborating statistical results and endorsing the hypothesis.

Year2024
Conference2024 International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies
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CompletedNov 2024
Accepted02 Nov 2024
Deposited20 Dec 2024
Copyright holder© 2024 The Authors
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Wen, J., Fu, C. H. Y., Tosun, D., Veturi, Y., Yang, Z., Abdulkadir, A., Mamourian, E., Srinivasan, D., Skampardoni, I., Singh, A., Nawani, H., Bao, J., Erus, G., Shou, H., Habes, M., Doshi, J., Varol, E., Mackin, R. S., Sotiras, A., Fan, Y., Saykin, A. J., Sheline, Y. I., Shen, L., Ritchie, M. D., Wolk, D. A., Albert, M., Resnick, S. M. and Davatzikos, C. 2022. Characterizing Heterogeneity in Neuroimaging, Cognition, Clinical Symptoms, and Genetics Among Patients With Late-Life Depression. JAMA Psychiatry. 79 (5), pp. 464-474. https://doi.org/10.1001/jamapsychiatry.2022.0020
An Effective Random Generalised Linear Model to Predict COPD
Saraireh, L., Sharif, S. and Alsallal, M. 2022. An Effective Random Generalised Linear Model to Predict COPD. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990712
Digital Data Extraction for Vehicles Forensic Investigation
Stathers, C., Muhammad, M., Fasanmade, A., Al-Bayatti, A., Morden, J. and Sharif, S. 2022. Digital Data Extraction for Vehicles Forensic Investigation. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990620
An Effective Galaxy Classification Using Fractal Analysis and Neural Network
Radhamani, P. S., Sharif, S. and Elmedany, W. 2022. An Effective Galaxy Classification Using Fractal Analysis and Neural Network. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990776
Evaluating the Stressful Commutes Using Physiological Signals and Machine Learning Techniques
Sharif, S., Theeng Tamang, M. and Fu, C. 2022. Evaluating the Stressful Commutes Using Physiological Signals and Machine Learning Techniques. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990849
Effective Machine Learning Based Techniques for Predicting Depression
Sharif, S., Zorto, A., Kareem, A. T. and Hafidh, R. 2022. Effective Machine Learning Based Techniques for Predicting Depression. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990824
Enhancement Techniques for Improving Facial Recognition Performance in Convolutional Neural Networks
Sharif, S., Olusegun, M., Zorto, A. and Elmedany, W. 2022. Enhancement Techniques for Improving Facial Recognition Performance in Convolutional Neural Networks. 3ICT 2022: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. University of Bahrain, Bahrain 20 - 21 Nov 2022 IEEE. https://doi.org/10.1109/3ICT56508.2022.9990811
Transcranial direct current stimulation effects in late life depression: a meta-analysis of individual participant data
Rimmer, R., Costafreda, S. G., Mutz, J., Joseph, K., Brunoni, A. R., Loo, C. K., Padberg, F., Palm, U. and Fu, C. 2022. Transcranial direct current stimulation effects in late life depression: a meta-analysis of individual participant data. Journal of Affective Disorders Reports. (Art. 100407). https://doi.org/10.1016/j.jadr.2022.100407
Adjunctive home-based transcranial direct current stimulation treatment for major depression with real-time remote supervision: An open-label, single-arm feasibility study with long term outcomes
Woodham, R., Rimmer, R., Young, A. H. and Fu, C. 2022. Adjunctive home-based transcranial direct current stimulation treatment for major depression with real-time remote supervision: An open-label, single-arm feasibility study with long term outcomes. Journal of Psychiatric Research. 153, pp. 197-205. https://doi.org/10.1016/j.jpsychires.2022.07.026
A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings
Wall, J., Poobalasingam, V., Sharif, S., Moniri, M., Glackin, C. and Cannings, N. 2022. A Mixed Reality Approach for dealing with the Video Fatigue of Online Meetings. 7th International XR Conference. Lisbon, Portugal 27 - 29 Apr 2022
Situational factors shape moral judgments in the trolley dilemma in Eastern, Southern, and Western countries in a culturally diverse sample
Bago, B., Kovacs, M., Protzko, J., Nagy, T., Kekecs, Z., Palfi, B., Adamkovic, M., Adamus, S., Albalooshi, S., Albayrak-Aydemir, N., Alper, S., Alvarez-Solas, S., Alves, S. G., Amaya, S., Andresen, P. K., Anjum, G., Ansari, D., Arriaga, P., Aruta, J. J. B. R., Arvanitis, A., Babincak, P., Barzykowski, K., Bashour, B., Baskin, E., Batalha, L., Batres, C., Bavolar, J., Bayrak, F., Becker, M., Becker, B., Belaus, A., Białek, M., Bilancini, E., Boller, D., Boncinelli, L., Boudesseul, J., Brown, B. T., Buchanan, E. M., Butt, M. M., Calvillo, D. P., Carnes, N. C., Castille, C. M., Celniker, J. B., Chartier, C. R., Chopik, W. J., Chotikavan, P., Chuan-Peng, H., Clancy, R. F., Çoker, O., Correia, R. C., Adoric, V. C., Cubillas, C. P., Czoschke, S., Daryani, Y., de Grefte, J. A. M., de Vries, W. C., Demirag Burak, E. G., Dias, C., Dixson, B. J. W., Du, X., Dumančić, F., Dumbravă, A., Dutra, N. B., Enachescu, J., Esteban-Serna, C., Eudave, L., Evans, T. R., Feldman, G., Felisberti, F. M., Fiedler, S., Findor, A., Fleischmann, A., Foroni, F., Francová, R., Frank, D-A., Fu, C., Gao, S., Ghasemi, O., Ghazi-Noori, A., Ghossainy, M. E., Giammusso, I., Gill, T., Gjoneska, B., Gollwitzer, M., Graton, A., Grinberg, M., Groyecka-Bernard, A., Harris, E. A., Hartanto, A., Hassan, W. A. N. M., Hatami, J., Heimark, K. R., Hidding, J. J. J., Hristova, E., Hruška, M., Hudson, C. A., Huskey, R., Ikeda, A., Inbar, Y., Ingram, G. P. D., Isler, O., Isloi, C., Iyer, A., Jaeger, B., Janssen, S. M. J., Jiménez-Leal, W., Jokić, B., Kačmár, P., Kadreva, V., Kaminski, G., Karimi-Malekabadi, F., Kasper, A. T A., Kendrick, K. M., Kennedy, B. J., Kocalar, H. E., Kodapanakkal, R. I., Kowal, M., Kruse, E., Kučerová, L., Kühberger, A., Kuzminska, A. O., Lalot, F., Lamm, C., Lammers, J., Lange, E. B., Lantian, A., Lau, I. Y.-M., Lazarevic, L. B., Leliveld, M. C., Lenz, J. N., Levitan, C. A., Lewis, S. C., Li, M., Li, Y., Li, H., Lima, T. J. S., Lins, S., Liuzza, M. T., Lopes, P., Lu, J. G., Lynds, T., Máčel, M., Mackinnon, S. P., Maganti, M., Magraw-Mickelson, Z., Magson, L. F., Manley, H., Marcu, G. M., Maslić Seršić, D., Matibag, C-J., Mattiassi, A. D. A., Mazidi, M., McFall, J. P., McLatchie, N., Mensink, M. C., Miketta, L., Milfont, T. L., Mirisola, A., Misiak, M., Mitkidis, P., Moeini-Jazani, M., Monajem, A., Moreau, D., Musser, E. D., Narhetali, E., Nuralfian, I., Ochoa, D. P., Olsen, J., Owsley, N. C., Özdoğru, A. A., Panning, M., Papadatou-Pastou, M., Parashar, N., Pärnamets, P., Paruzel-Czachura, M., Parzuchowski, M., Paterlini, J. V., Pavlacic, J. M., Peker, M., Peters, K., Piatnitckaia, L., Pinto, I., Policarpio, M. R., Pop-Jordanova, N., Pratama, A. J., Primbs, M. A., Pronizius, E., Purić, D., Puvia, E., Qamari, V., Qian, K., Quiamzade, A., Ráczová, B., Reinero, D. A., Reips, U-D., Reyna, C., Reynolds, K., Ribeiro, M. F. F., Röer, J. P., Ross, R. M., Roussos, P., Ruiz-Dodobara, F., Ruiz-Fernandez, S., Rutjens, B. T., Rybus, K., Samekin, A., Santos, A. C., Say, N., Schild, C., Schmidt, K., Ścigała, K. A., Sharifian, M. H., Qureshi, J., Shi, Y., Sievers, E., Sirota, M., Slipenkyj, M., Solak, C., Sorokowska, A., Sorokowski, P., Söylemez, S., Steffens, N. K., Stephen, I. D., Sternisko, A., Stevens-Wilson, L., Stewart, S. L. K., Stieger, S., Storage, D., Strube, J., Susa, K. J., Szekely-Copîndean, R. D., Szostak, N. M., Takwin, B., Tatachari, S., Thomas, A. G., Tiede, K. E., Tiong, L. E., Tonković, M., Trémolière, B., Tunstead, L. V., Türkan, B. N., Twardawski, M., Vadillo, M. A., Vally, Z., Vaughn, L. A., Verschuere, B., Vlašiček, D., Voracek, M., Vranka, M. A., Wang, S., West, S-L., Whyte, S., Wilton, L. S., Wlodarczyk, A., Wu, X., Xin, F., Yadanar, S., Yama, H., Yamada, Y., Yilmaz, O., Yoon, S., Young, D. M., Zakharov, I., Zein, R. A., Zettler, I., Žeželj, I. L., Zhang, D. C., Zhang, J., Zheng, X., Hoekstra, R. and Aczel, B. 2022. Situational factors shape moral judgments in the trolley dilemma in Eastern, Southern, and Western countries in a culturally diverse sample. Nature Human Behaviour. 6, pp. 880-895. https://doi.org/10.1038/s41562-022-01319-5
Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach
Sharif, S., Theeng Tamang, M. and Fu, C. 2021. Predicting the Health Impacts of Commuting Using EEG Signal Based on Intelligent Approach. 3ICT 2021: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. Bahrain, University of Bahrain 29 - 30 Sep 2021 IEEE. https://doi.org/10.1109/3ICT53449.2021.9582119
An Effective Hybrid Approach Based on Machine Learning Techniques for Auto-Translation: Japanese to English
Sharif, S., Auwal, B., Maltby, H. and Al-Bayatti, A. 2021. An Effective Hybrid Approach Based on Machine Learning Techniques for Auto-Translation: Japanese to English. 3ICT 2021: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. Bahrain, University of Bahrain 29 - 30 Sep 2021 IEEE. https://doi.org/10.1109/3ICT53449.2021.9581629
An Effective Cost-Sensitive Convolutional Neural Network for Network Traffic Classification
Sharif, S. and Moein, M. 2021. An Effective Cost-Sensitive Convolutional Neural Network for Network Traffic Classification. 3ICT 2021: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. Bahrain, University of Bahrain 29 - 30 Sep 2021 IEEE. https://doi.org/10.1109/3ICT53449.2021.9581789
Defeating the Credit Card Scams Through Machine Learning Algorithms
Bains, K., Fasanmade, A., Morden, J., Al-Bayatti, A. H., Sharif, S. and Alfakeeh, A. S. 2021. Defeating the Credit Card Scams Through Machine Learning Algorithms. 3ICT 2021: International Conference on Innovation and Intelligence for Informatics, Computing, and Technologies. Bahrain, University of Bahrain 29 - 30 Sep 2021 IEEE. https://doi.org/10.1109/3ICT53449.2021.9582060
Observing infants together: long-term experiences of observers and families
Papoutsi, V and Fu, C. 2021. Observing infants together: long-term experiences of observers and families. Infant Observation. 24 (1), pp. 4-22. https://doi.org/10.1080/13698036.2021.1952094
Motor adaptation and internal model formation in a robot-mediated forcefield
Taga, M., Curci, A., Pizzamiglio, S., Lacal, I., Turner, D. and Fu, C. 2021. Motor adaptation and internal model formation in a robot-mediated forcefield. Psychoradiology. 1 (2), p. 73–87. https://doi.org/10.1093/psyrad/kkab007
Is tDCS a potential first line treatment for major depression?
Woodham, R., Rimmer, R., Mutz, J. and Fu, C. 2021. Is tDCS a potential first line treatment for major depression? International Review of Psychiatry. 33 (3), pp. 250-265. https://doi.org/10.1080/09540261.2021.1879030
Dehydration in older people: a systematic review of the effects of dehydration on health outcomes, healthcare costs and cognitive performance
Edmonds, C., Foglia, E., Booth, P., Fu, C. and Gardner, M. 2021. Dehydration in older people: a systematic review of the effects of dehydration on health outcomes, healthcare costs and cognitive performance. Archives of Gerontology and Geriatrics. 95 (Art. 104380). https://doi.org/10.1016/j.archger.2021.104380
Dictionary selection for Compressed Sensing of EEG signals using sparse binary matrix and spatiotemporal sparse Bayesian learning
Dey, M., Shiraz, A., Sharif, S., Lota, J. and Demosthenous, A. 2020. Dictionary selection for Compressed Sensing of EEG signals using sparse binary matrix and spatiotemporal sparse Bayesian learning. Biomedical Physics and Engineering Express. 6 (Art. 065024). https://doi.org/10.1088/2057-1976/abc133
An Effective Knowledge-Based Modeling Approach towards a “Smart-School Care Coordination System” for Children and Young People with Special Educational Needs and Disabilities
Hafidh, R., Sharif, S., Al-Bayatti, A. H., Alfakeeh, A. S., Alassafi, M. O. and Alqarni, M. A. 2020. An Effective Knowledge-Based Modeling Approach towards a “Smart-School Care Coordination System” for Children and Young People with Special Educational Needs and Disabilities. Symmetry. 12 (Art. 1495). https://doi.org/10.3390/sym12091495
A Machine-Learning-Based Approach to Predict the Health Impacts of Commuting in Large Cities: Case Study of London
Raj Theeng Tamang, M., Sharif, M. S., Al-Bayatti, A. H., Alfakeeh, A. S. and Omar Alsayed, A. 2020. A Machine-Learning-Based Approach to Predict the Health Impacts of Commuting in Large Cities: Case Study of London. Symmetry. 12 (Art. 866). https://doi.org/10.3390/sym12050866
Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes
Okoye, K., Islam, S., Naeem, U. and Sharif, S. 2020. Semantic-Based Process Mining Technique for Annotation and Modelling of Domain Processes. International Journal of Innovative Computing, Information and Control. 16 (3), pp. 899-921. https://doi.org/10.24507/ijicic.16.03.899
Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders
Writing Committee for the Attention-Deficit/Hyperactivity Disorder, Autism Spectrum Disorder, Bipolar Disorder, Major Depressive Disorder, Obsessive-Compulsive Disorder, and Schizophrenia ENIGMA Working Groups 2020. Virtual Histology of Cortical Thickness and Shared Neurobiology in 6 Psychiatric Disorders. JAMA Psychiatry. 78 (1), p. 47–63. https://doi.org/10.1001/jamapsychiatry.2020.2694
ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing
Schmaal, L., Pozzi, E., Ho, T. C., van Velzen, L. S., Veer, I. M., Opel, N., Van Someren, E. J. W., Han, L. K. M., Aftanas, L., Aleman, A., Baune, B. T., Berger, K., Blanken, T. F., Capitão, L., Couvy-Duchesne, B., Cullen, K. R., Dannlowski, U., Davey, C., Erwin-Grabner, T., Evans, J., Frodl, T., Fu, C., Godlewska, B., Gotlib, I. H., Goya-Maldonado, R., Grabe, H. J., Groenewold, N. A., Grotegerd, D., Gruber, O., Gutman, B. A., Hall, G. B., Harrison, B. J., Hatton, S. N., Hermesdorf, M., Hickie, I. B., Hilland, E., Irungu, B., Jonassen, R., Kelly, S., Kircher, T., Klimes-Dougan, B., Krug, A., Landrø, N. I., Lagopoulos, J., Leerssen, J., Li, M., Linden, D. E. J., MacMaster, F. P., McIntosh, A. M., Mehler, D. M. A., Nenadić, I., Penninx, B. W. J. H., Portella, M. J., Reneman, L., Rentería, M. E., Sacchet, M. D., Sämann, P. G., Schrantee, A., Sim, K., Soares, J. C., Stein, D. J., Tozzi, L., van Der Wee, N. J. A., van Tol, M., Vermeiren, R., Vives-Gilabert, Y., Walter, H., Walter, M., Whalley, H. C., Wittfeld, K., Whittle, S., Wright, M. J., Yang, T. T., Zarate Jr, C., Thomopoulos, S. I., Jahanshad, N., Thompson, P. M. and Veltman, D. J. 2020. ENIGMA MDD: seven years of global neuroimaging studies of major depression through worldwide data sharing. Translational Psychiatry . 10 (Art. 172). https://doi.org/10.1038/s41398-020-0842-6
Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software
Lowe, G., Spottiswoode, B., Declerck, J., Sullivan,, K., Sharif, S., Wong, W. and Sanghera, B. 2020. Positron emission tomography PET/CT harmonisation study of different clinical PET/CT scanners using commercially available software. BJR Open. 2 (Art. 20190035). https://doi.org/10.1259/bjro.20190035
Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group
Han, L. K. M., Dinga, R., Hahn, T., Ching, C. R. K., Eyler, L. T., Aftanas, L., Aghajani, M., Aleman, A., Baune, B. T., Berger, K., Brak, I., Filho, G. B., Carballedo, A., Connolly, C. G., Couvy-Duchesne, B., Cullen, K. R., Dannlowski, U., Davey, C. G., Dima, D., Duran, F. L. S., Enneking, V., Filimonova, E., Frenzel, S., Frodl, T., Fu, C., Godlewska, B. R., Gotlib, I. H., Grabe, H. J., Groenewold, N. A., Grotegerd, D., Gruber, O., Hall, G. B., Harrison, B. J., Hatton, S. N., Hermesdorf, M., Hickie, I. B., Ho, T. C., Hosten, N., Jansen, A., Kähler, B., Kircher, T., Klimes-Dougan, B., Krämer, B., Krug, A., Lagopoulos, J., Leenings, R., MacMaster, F. P., MacQueen, G., McIntosh, A., McLellan, Q., McMahon, K. L., Medland, S. E., Mueller, B. A., Mwangi, B., Osipov, E., Portella, M. J., Pozzi, E., Reneman, L., Repple, J., Rosa, P. G. P., Sacchet, M. D., Sämann, P. G., Schnell, K., Schrantee, A., Simulionyte, E., Soares, J. C., Sommer, J., Stein, D. J., Steinsträter, O., Strike, L. T., Thomopoulos, S. I., van Tol, M., Veer, I. M., Vermeiren, R. R. J. M., Walter, H., van der Wee, N. J. A., van der Werff, S. J. A., Whalley, H., Winter, N. R., Wittfeld, K., Wright, M. J., Wu, M., Völzke, H., Yang, T. T., Zannias, V., de Zubicaray, G. I., Zunta-Soares, G. B., Abé, C., Alda, M., Andreassen, O. A., Bøen, E., Bonnin, C. M., Canales-Rodriguez, E. J., Cannon, D., Caseras, X., Chaim-Avancini, T. M., Elvsåshagen, T., Favre, P., Foley, S. F., Fullerton, J. M., Goikolea, J. M., Haarman, B. C. M., Hajek, T., Henry, C., Houenou, J., Howells, F. M., Ingvar, M., Kuplicki, R., Lafer, B., Landén, M., Machado-Vieira, R., Malt, U. F., McDonald, C., Mitchell, P. B., Nabulsi, L., Concepcion Garcia Otaduy, M., Overs, B. J., Polosan, M., Pomarol-Clotet, E., Radua, J., Rive, M. M., Roberts, G., Ruhe, H. G., Salvador, R., Sarró, S., Satterthwaite, T. D., Savitz, J., Schene, A. H., Schofield, P. R., Serpa, M. H., Sim, K., Gerhardt Soeiro-de-Souza, M., Sutherland, A. N., Temmingh, H. S., Timmons, G. M., Uhlmann, A., Vieta, E., Wolf, D. H., Zanetti, M. V., Jahanshad, N., Thompson, P. M., Veltman, D. J., Penninx, B. W. J. H., Marquand, A. F., Cole J. H. and Schmaal, L. 2020. Brain aging in major depressive disorder: results from the ENIGMA major depressive disorder working group. Molecular Psychiatry. 26, pp. 5124-5139. https://doi.org/10.1038/s41380-020-0754-0
An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study
Sharif, S., Abbod, M., Al-Bayatti, A., Amira, A., Alfakeeh, A. and Sanghera, B. 2020. An Accurate Ensemble Classifier for Medical Volume Analysis: Phantom and Clinical PET Study. IEEE Access. 8, pp. 37482-37494. https://doi.org/10.1109/ACCESS.2020.2975135
Brain-derived neurotrophic factor association with amygdala response in major depressive disorder
Lorenzetti, V., Costafreda, S. G., Rimmer, R., Rasenick, M. M., Marangell, L. B. and Fu, C. 2020. Brain-derived neurotrophic factor association with amygdala response in major depressive disorder. Journal of Affective Disorders. 267, pp. 103-106. https://doi.org/10.1016/j.jad.2020.01.159
The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project
Arias, J. A., Williams, C., Raghvani, R., Aghajani, M., Baez, S., Belzung, C., Booij, L., Busatto, G., Chiarella, J., Fu, C., Ibanez, A., Liddell, B. J., Lowe, L., Penninx, B. W. J. H., Rosa, P. and Kemp, A. H. 2020. The Neuroscience of Sadness: A Multidisciplinary Synthesis and Collaborative Review for the Human Affectome Project. Neuroscience & Biobehavioral Reviews. 111, pp. 199-228. https://doi.org/10.1016/j.neubiorev.2020.01.006
Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All
Ebenuwa, S., Sharif, S., Al-Nemrat, A., Al-Bayatti, A. H., Alalwan, N., Alzahrani, A. I. and Alfarraj, O. 2019. Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All. Symmetry. 11 (Art. 1504). https://doi.org/10.3390/sym11121504
Policy-Based Security Management System for 5G Heterogeneous Networks
Alquhayz, H., Alalwan, N., Alzahrani, A. I., Al-Bayatti, A. H. and Sharif, S. 2019. Policy-Based Security Management System for 5G Heterogeneous Networks. Wireless Communications and Mobile Computing. 2019 (Art. 4582391). https://doi.org/10.1155/2019/4582391
A Framework for Augmented Reality Based Shared Experiences
Ali, A., Glackin, C., Cannings, N., Wall, J., Sharif, S. and Moniri, M. 2019. A Framework for Augmented Reality Based Shared Experiences. Immersive Learning Research Network - iLRN. London, UK 23 - 27 Jun 2019 Technischen Universität Graz. https://doi.org/10.3217/978-3-85125-657-4-24
Addressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers
Fu, C., Fan, Y. and Davatzikos, C. 2019. Addressing heterogeneity (and homogeneity) in treatment mechanisms in depression and the potential to develop diagnostic and predictive biomarkers. NeuroImage: Clinical. 24 (Art.101997). https://doi.org/10.1016/j.nicl.2019.101997
A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images
Van Druten, J., Sharif, S., Chan, S. S., Chong, C. and Abdalla, H. 2019. A Deep Learning Based Suggested Model to Detect Necrotising Enterocolitis in Abdominal Radiography Images. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. https://doi.org/10.1109/iCCECE46942.2019.8941615
Context-Aware Driver Distraction Severity Classification using LSTM Network
Fasanmade, A., Aliyu, S., He, Y., Al-Bayatti, A. H., Sharif, S. and Alfakeeh, A. S. 2019. Context-Aware Driver Distraction Severity Classification using LSTM Network. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. pp. 147-152 https://doi.org/10.1109/iCCECE46942.2019.8941966
Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model
Sharif, S., Al-Bayatti, A. H. and Alfakeeh, A. S. 2019. Predicting the Standard and Deviant Patterns In EEG Signals Based On Deep Learning Model. IEEE International Conference on Computing, Electronics & Communications Engineering 2019 (IEEE iCCECE '19) . London Metropolitan University, London, UK 22 - 23 Aug 2019 IEEE. https://doi.org/10.1109/iCCECE46942.2019.8941730
Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake
Hirji, H., Sullivan, K., Lasker, I., Sharif, S., Nunes, A., Shepherd, C., Wong, W. and Sanghera, B. 2019. Effect of PET Image Reconstruction Techniques on Unexpected Aorta Uptake. Molecular Imaging and Radionuclide Therapy. 28 (1), pp. 1-7. https://doi.org/10.4274/mirt.galenos.2018.88528
Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data
Ebenuwa, S., Sharif, M., Alazab, Mamoun and Al-Nemrat, A. 2019. Variance Ranking Attributes Selection Techniques for Binary Classification Problem in Imbalance Data. IEEE Access. 7, pp. 24649-24666. https://doi.org/10.1109/ACCESS.2019.2899578
Comparative efficacy and acceptability of non-surgical brain stimulation for the acute treatment of major depressive episodes in adults: systematic review and network meta-analysis
Mutz, Julian, Vipulananthan, Vijeinika, Carter, Ben, Hurlemann, René, Fu, C. and Young, Allan H. 2019. Comparative efficacy and acceptability of non-surgical brain stimulation for the acute treatment of major depressive episodes in adults: systematic review and network meta-analysis. BMJ. 364, p. Art. l1079. https://doi.org/10.1136/bmj.l1079
Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body
Sharif, M. and Alsibai, Mohammed Hayyan 2018. Medical data analysis based on Nao robot: An automated approach towards robotic real-time interaction with human body. in: 2017 7th IEEE International Conference on Control System, Computing and Engineering (ICCSCE) IEEE. pp. 91-96
A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis
van Druten, Jacqueline, Sharif, M., Khashu, Minesh and Abdalla, H. 2019. A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis. in: Miraz, Mahdi H., Exce, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 101-106
A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser
Alsallal, Muna, Sharif, M., Al-Ghzawi, Baydaa and al Mutoki, Sabah Mohammed Mlkat 2019. A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser. in: Miraz, Mahdi H., Excell, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 118-122
A systematic review and meta-analysis of the neural correlates of psychological therapies in major depression
Sankar, Anjali, Melin, Alice, Lorenzetti, Valentina, Horton, Paul, Costafreda, Sergi G. and Fu, C. 2018. A systematic review and meta-analysis of the neural correlates of psychological therapies in major depression. Psychiatry Research: Neuroimaging. 279, pp. 31-39. https://doi.org/10.1016/j.pscychresns.2018.07.002
Efficacy and acceptability of non-invasive brain stimulation for the treatment of adult unipolar and bipolar depression: A systematic review and meta-analysis of randomised sham-controlled trials
Mutz, Julian, Edgcumbe, Daniel R., Brunoni, Andre R. and Fu, C. 2018. Efficacy and acceptability of non-invasive brain stimulation for the treatment of adult unipolar and bipolar depression: A systematic review and meta-analysis of randomised sham-controlled trials. Neuroscience & Biobehavioral Reviews. 92, pp. 291-303. https://doi.org/10.1016/j.neubiorev.2018.05.015
Predictors of amygdala activation during the processing of emotional stimuli: A meta-analysis of 385 PET and fMRI studies
Costafreda, Sergi G., Brammer, Michael J., David, Anthony S. and Fu, C. 2007. Predictors of amygdala activation during the processing of emotional stimuli: A meta-analysis of 385 PET and fMRI studies. Brain Research Reviews. 58 (1), pp. 57-70. https://doi.org/10.1016/j.brainresrev.2007.10.012
Neural basis of the emotional Stroop interference effect in major depression
Mitterschiffthaler, M. T., Williams, S. C. R., Walsh, N. D., Cleare, A. J., Donaldson, C., Scott, J. and Fu, C. 2008. Neural basis of the emotional Stroop interference effect in major depression. Psychological Medicine. 38 (02), pp. 247-256. https://doi.org/10.1017/S0033291707001523
Pattern Classification of Sad Facial Processing: Toward the Development of Neurobiological Markers in Depression
Fu, C., Mourao-Miranda, Janaina, Costafreda, Sergi G., Khanna, Akash, Marquand, Andre F., Williams, Steve C.R. and Brammer, Michael J. 2008. Pattern Classification of Sad Facial Processing: Toward the Development of Neurobiological Markers in Depression. Biological Psychiatry. 63 (7), pp. 656-662. https://doi.org/10.1016/j.biopsych.2007.08.020
Neural Responses to Sad Facial Expressions in Major Depression Following Cognitive Behavioral Therapy
Fu, C., Williams, Steven C.R., Cleare, Anthony J., Scott, Jan, Mitterschiffthaler, Martina T., Walsh, Nicholas D., Donaldson, Catherine, Suckling, John, Andrew, Chris, Steiner, Herbert and Murray, Robin M. 2008. Neural Responses to Sad Facial Expressions in Major Depression Following Cognitive Behavioral Therapy. Biological Psychiatry. 64 (6), pp. 505-512. https://doi.org/10.1016/j.biopsych.2008.04.033
Neuroanatomy of verbal working memory as a diagnostic biomarker for depression
Marquand, Andre F., Mourão-Miranda, Janaina, Brammer, Michael J., Cleare, Anthony J. and Fu, C. 2008. Neuroanatomy of verbal working memory as a diagnostic biomarker for depression. NeuroReport. 19 (15), pp. 1507-1511. https://doi.org/10.1097/WNR.0b013e328310425e
Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression
Costafreda, Sergi G., Khanna, Akash, Mourao-Miranda, Janaina and Fu, C. 2009. Neural correlates of sad faces predict clinical remission to cognitive behavioural therapy in depression. NeuroReport. 20 (7), pp. 637-641. https://doi.org/10.1097/WNR.0b013e3283294159
Amygdala activation to masked happy facial expressions
Juruena, Mario F., Giampietro, Vincent P., Smith, Stephen D., Surguladze, Simon A., Dalton, Jeffrey A., Benson, Philip J., Cleare, Anthony J. and Fu, C. 2010. Amygdala activation to masked happy facial expressions. Journal of the International Neuropsychological Society. 16 (02), pp. 383-387. https://doi.org/10.1017/S1355617709991172
Subregional hippocampal deformations in major depressive disorder
Cole, James, Toga, Arthur W., Hojatkashani, Cornelius, Thompson, Paul, Costafreda, Sergi G., Cleare, Anthony J., Williams, Steven C.R., Bullmore, Edward T., Scott, Jan L., Mitterschiffthaler, Martina T., Walsh, Nicholas D., Donaldson, Catherine, Mirza, Mubeena, Marquand, Andre, Nosarti, Chiara, McGuffin, Peter and Fu, C. 2010. Subregional hippocampal deformations in major depressive disorder. Journal of Affective Disorders. 126 (1-2), pp. 272-277. https://doi.org/10.1016/j.jad.2010.03.004
Ketamine-Induced Disruption of Verbal Self-Monitoring Linked to Superior Temporal Activation
Stone, J. M., Abel, K. M., Allen, M.P.G., van Haren, N., Matsumoto, K., McGuire, P. K. and Fu, C. 2010. Ketamine-Induced Disruption of Verbal Self-Monitoring Linked to Superior Temporal Activation. Pharmacopsychiatry. 44 (1), pp. 33-48. https://doi.org/10.1055/s-0030-1267942
Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression
Nouretdinov, Ilia, Costafreda, Sergi G., Gammerman, Alexander, Chervonenkis, Alexey, Vovk, Vladimir, Vapnik, Vladimir and Fu, C. 2011. Machine learning classification with confidence: Application of transductive conformal predictors to MRI-based diagnostic and prognostic markers in depression. NeuroImage. 56 (2), pp. 809-813. https://doi.org/10.1016/j.neuroimage.2010.05.023
Cortisol responses to serial MRI scans in healthy adults and in depression
Peters, Sabine, Cleare, Anthony J., Papadopoulos, Andrew and Fu, C. 2011. Cortisol responses to serial MRI scans in healthy adults and in depression. Psychoneuroendocrinology. 36 (5), pp. 737-741. https://doi.org/10.1016/j.psyneuen.2010.10.009
No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression
Cole, J., Weinberger, D. R., Mattay, V. S., Cheng, X., Toga, A. W., Thompson, P. M., Powell-Smith, G., Cohen-Woods, S., Simmons, A., McGuffin, P. and Fu, C. 2011. No effect of 5HTTLPR or BDNF Val66Met polymorphism on hippocampal morphology in major depression. Genes, Brain and Behavior. 10 (7), pp. 756-764. https://doi.org/10.1111/j.1601-183X.2011.00714.x
Hippocampal atrophy in first episode depression: A meta-analysis of magnetic resonance imaging studies
Cole, James, Costafreda, Sergi G., McGuffin, Peter and Fu, C. 2011. Hippocampal atrophy in first episode depression: A meta-analysis of magnetic resonance imaging studies. Journal of Affective Disorders. 134 (1-3), pp. 483-487. https://doi.org/10.1016/j.jad.2011.05.057
Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function
Pauli, Andreina, Prata, Diana P., Mechelli, Andrea, Picchioni, Marco, Fu, C., Chaddock, Christopher A., Kane, Fergus, Kalidindi, Sridevi, McDonald, Colm, Kravariti, Eugenia, Toulopoulou, Timothea, Bramon, Elvira, Walshe, Muriel, Ehlert, Natascha, Georgiades, Anna, Murray, Robin, Collier, David A. and McGuire, Philip 2012. Interaction between effects of genes coding for dopamine and glutamate transmission on striatal and parahippocampal function. Human Brain Mapping. 34 (9), pp. 2244-2258. https://doi.org/10.1002/hbm.22061
White matter abnormalities and illness severity in major depressive disorder
Cole, James, Chaddock, Christopher A., Farmer, Anne E., Aitchison, Katherine J., Simmons, Andrew, McGuffin, Peter and Fu, C. 2012. White matter abnormalities and illness severity in major depressive disorder. British Journal of Psychiatry. 201 (01), pp. 33-39. https://doi.org/10.1192/bjp.bp.111.100594
Predictive neural biomarkers of clinical response in depression: A meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies
Fu, C., Steiner, Herbert and Costafreda, Sergi G. 2013. Predictive neural biomarkers of clinical response in depression: A meta-analysis of functional and structural neuroimaging studies of pharmacological and psychological therapies. Neurobiology of Disease. 52, pp. 75-83. https://doi.org/10.1016/j.nbd.2012.05.008
Modulation of amygdala response and connectivity in depression by serotonin transporter polymorphism and diagnosis
Costafreda, Sergi G., McCann, Peter, Saker, Pascal, Cole, James H., Cohen-Woods, Sarah, Farmer, Anne E., Aitchison, Katherine J., McGuffin, Peter and Fu, C. 2013. Modulation of amygdala response and connectivity in depression by serotonin transporter polymorphism and diagnosis. Journal of Affective Disorders. 150 (1), pp. 96-103. https://doi.org/10.1016/j.jad.2013.02.028
Modafinil Augmentation Therapy in Unipolar and Bipolar Depression
Goss, Alexander J., Kaser, Muzaffer, Costafreda, Sergi G., Sahakian, Barbara J. and Fu, C. 2013. Modafinil Augmentation Therapy in Unipolar and Bipolar Depression. The Journal of Clinical Psychiatry. 74 (11), pp. 1101-1107. https://doi.org/10.4088/JCP.13r08560
Other race effect on amygdala response during affective facial processing in major depression
Sankar, Anjali, Costafreda, Sergi G., Marangell, Lauren B. and Fu, C. 2018. Other race effect on amygdala response during affective facial processing in major depression. Neuroscience Letters. 662, pp. 381-384. https://doi.org/10.1016/j.neulet.2017.10.043
An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements
Alsibai, Mohammed Hayyan, Sharif, M., Yaakub, Salma and Hamran, Nurul Nadia Nor 2018. An Innovative EPW Design Using Add-on Features to Meet Malaysian Requirements. in: Proceedings of the 7th IEEE International Conference on Control Systems, Computing and Engineering (ICCSCE 2017) IEEE. pp. 180-185
An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes
Sharif, M., Alsallal, Muna and Herghelegiu, Lucian 2018. An Effective TeleHealth Assistive System to Support Senior Citizen at Home or Care-Homes. IEEE International Conference on Computing, Electronics & Communications Engineering 2018 (iCCECE '18). Southend, UK 16 - 17 Aug 2018 IEEE. pp. 113-117 https://doi.org/10.1109/iCCECOME.2018.8658877
The effect of psychosis associated CACNA1C, and its epistasis with ZNF804A, on brain function
Tecelão, Diogo, Mendes, Ana, Martins, Daniel, Fu, C., Chaddock, Christopher A, Picchioni, Marco M, McDonald, Colm, Kalidindi, Sridevi, Murray, Robin and Prata, Diana P 2018. The effect of psychosis associated CACNA1C, and its epistasis with ZNF804A, on brain function. Genes, Brain and Behavior. 18 (4), p. e12510. https://doi.org/10.1111/gbb.12510
Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder
Inkster, Becky, Simmons, Andy, Cole, James, Schoof, Erwin, Linding, Rune, Nichols, Tom, Muglia, Pierandrea, Holsboer, Florian, Saemann, Philipp, McGuffin, Peter, Fu, C., Miskowiak, Kamilla, Matthews, Paul M., Zai, Gwyneth and Nicodemus, Kristin 2018. Unravelling the GSK3β-related genotypic interaction network influencing hippocampal volume in recurrent major depressive disorder. Psychiatric Genetics. 28 (5), pp. 77-84. https://doi.org/10.1097/YPG.0000000000000203
Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition
Ranlund, Siri, Rosa, Maria Joao, de Jong, Simone, Cole, James H., Kyriakopoulos, Marinos, Fu, C., Mehta, Mitul A. and Dima, Danai 2018. Associations between polygenic risk scores for four psychiatric illnesses and brain structure using multivariate pattern recognition. NeuroImage: Clinical. 20, pp. 1026-1036. https://doi.org/10.1016/j.nicl.2018.10.008
Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network
Sharif, M., Naeem, U., Islam, S. and Karami, A. 2018. Functional Connectivity Evaluation for Infant EEG Signals based on Artificial Neural Network. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems Conference (IntelliSys) 2018. London, UK 06 - 07 Sep 2018 Springer, Cham. https://doi.org/10.1007/978-3-030-01057-7_34
The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain
Okoye, Kingsley, Islam, S., Naeem, U., Sharif, M., Azam, Muhammad Awais and Karami, A. 2018. The Application of a Semantic-Based Process Mining Framework on a Learning Process Domain. Arai, Kohei, Kapoor, Supriya and Bhatia, Rahul (ed.) Intelligent Systems Conference (IntelliSys) 2018. London, UK 06 - 07 Sep 2018 Springer, Cham. https://doi.org/10.1007/978-3-030-01054-6_96
Anodal transcranial direct current stimulation over the right dorsolateral prefrontal cortex enhances reflective judgment & decision-making
Edgcumbe, Daniel R., Thoma, V., Rivolta, Davide, Nitsche, Michael A. and Fu, C. 2018. Anodal transcranial direct current stimulation over the right dorsolateral prefrontal cortex enhances reflective judgment & decision-making. Brain Stimulation. 12 (3), pp. 652-658. https://doi.org/10.1016/j.brs.2018.12.003
Taskification – Gamification of Tasks
Naeem, U., Islam, S., Sharif, M., Sudakov, Sergey and Azam, Awais 2017. Taskification – Gamification of Tasks. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 631-634
SignalSense - Towards Quality Service
Islam, S., Sharif, M., Naeem, U. and Geehan, James 2017. SignalSense - Towards Quality Service. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 627-630
CrimeSafe - Helping you stay safe
Islam, S., Naeem, U., Sharif, M. and Dovnarovic, Arnold 2017. CrimeSafe - Helping you stay safe. in: Proceedings of the 2017 ACM International Joint Conference on Pervasive and Ubiquitous Computing and Proceedings of the 2017 ACM International Symposium on Wearable Computers Association for Computing Machinery (ACM). pp. 642-645
Effects of antidepressant therapy on neural components of verbal working memory in depression
Sankar, Anjali, Adams, Tracey M, Costafreda, Sergi G. and Fu, C. 2017. Effects of antidepressant therapy on neural components of verbal working memory in depression. Journal of Psychopharmacology. 31 (9), pp. 1176-1183. https://doi.org/10.1177/0269881117724594
Body mass index, but not FTO genotype or major depressive disorder, influences brain structure
Cole, J.H., Boyle, C.P., Simmons, A., Cohen-Woods, S., Rivera, M., McGuffin, P., Thompson, P.M. and Fu, C. 2013. Body mass index, but not FTO genotype or major depressive disorder, influences brain structure. Neuroscience. 252 (Nov.), pp. 109-117. https://doi.org/10.1016/j.neuroscience.2013.07.015
Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model
Zhu, Dajiang, Riedel, Brandalyn C., Jahanshad, Neda, Groenewold, Nynke A., Stein, Dan J., Gotlib, Ian H., Dima, Danai, Cole, James H., Fu, C., Walter, Henrik, Veer, Ilya M., Frodl, Thomas, Schmaal, Lianne, Veltman, Dick J. and Thompson, Paul M. 2017. Classification of Major Depressive Disorder via Multi-Site Weighted LASSO Model. in: Descoteaux, Maxime, Maier-Hein, Lena, Franz, Alfred, Jannin, Pierre, Collins, D. Louis and Duchesne, Simon (ed.) Medical Image Computing and Computer-Assisted Intervention − MICCAI 2017 Springer, Cham.
The Future of Enterprise Security with Regards to Mobile Technology and Applications
Tagoe, F. T. and Sharif, M. 2017. The Future of Enterprise Security with Regards to Mobile Technology and Applications. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles
Seuwou, Patrice, Banissi, Ebad, Ubakanma, George, Sharif, M. and Healey, Ann 2017. Actor-Network Theory as a Framework to Analyse Technology Acceptance Model’s External Variables: The Case of Autonomous Vehicles. in: Jahankhani, Hamid, Carlile, Alex, Emm, David, Hosseinian-Far, Amin, Brown, Guy, Sexton, Graham and Jamal, Arshad (ed.) Global Security, Safety and Sustainability - The Security Challenges of the Connected World. ICGS3 2017 Proceedings Springer International Publishing.
Recent Advances in Neuroimaging of Mood Disorders: Structural and Functional Neural Correlates of Depression, Changes with Therapy, and Potential for Clinical Biomarkers
Atkinson, Lauren, Sankar, Anjali, Adams, Tracey M. and Fu, C. 2014. Recent Advances in Neuroimaging of Mood Disorders: Structural and Functional Neural Correlates of Depression, Changes with Therapy, and Potential for Clinical Biomarkers. Current Treatment Options in Psychiatry. 1 (3), pp. 278-293. https://doi.org/10.1007/s40501-014-0022-5
Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis
Wise, T., Radua, J., Via, E., Cardoner, N., Abe, O., Adams, T. M., Amico, F., Cheng, Y., Cole, J. H., de Azevedo Marques Périco, C., Dickstein, D. P., Farrow, T. F. D., Frodl, T., Wagner, G., Gotlib, I. H., Gruber, O., Ham, B. J., Job, D. E., Kempton, M. J., Kim, M. J., Koolschijn, P. C. M. P., Malhi, G. S., Mataix-Cols, D., McIntosh, A. M., Nugent, A. C., O'Brien, J. T.., Pezzoli, S, Phillips, M. L., Sachdev, P. S., Salvadore, G., Selvaraj, S., Stanfield, A. C., Thomas, A. J., van Tol, M. J., van der Wee, N. J. A., Veltman, D. J., Young, A. H., Fu, C., Cleare, A. J. and Arnone, D. 2016. Common and distinct patterns of grey-matter volume alteration in major depression and bipolar disorder: evidence from voxel-based meta-analysis. Molecular Psychiatry. https://doi.org/10.1038/mp.2016.72
An efficient system for preprocessing confocal corneal images for subsequent analysis
Sharif, M., Qahwaji, Rami, Hayajneh, Sofyan, Ipson, Stanley, Alzubaidi, Rania and Brahma, Arun 2014. An efficient system for preprocessing confocal corneal images for subsequent analysis. in: 2014 14th UK Workshop on Computational Intelligence (UKCI) IEEE.
Artificial Neural Network-Based System for PET Volume Segmentation
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2010. Artificial Neural Network-Based System for PET Volume Segmentation. International Journal of Biomedical Imaging. 2010 (105610). https://doi.org/10.1155/2010/105610
Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification
Sharif, M., Abbod, Maysam, Amira, Abbes and Zaidi, Habib 2012. Artificial Neural Network-Statistical Approach for PET Volume Analysis and Classification. Advances in Fuzzy Systems. 2012 (327861). https://doi.org/10.1155/2012/327861
Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study
Sharif, M., Abbod, Maysam, Sonoda, Luke I. and Sanghera, Bal 2013. Machine Learning Optimisation for Realistic 2D and 3D PET-CT Phantom Study. British Journal of Applied Science & Technology. 4 (4), pp. 634-649. https://doi.org/10.9734/bjast/2014/5084
Preparation of 2D sequences of corneal images for 3D model building
Elbita, Abdulhakim, Qahwaji, Rami, Ipson, Stanley, Sharif, M. and Ghanchi, Faruque 2015. Preparation of 2D sequences of corneal images for 3D model building. Computer Methods and Programs in Biomedicine. 114 (2), pp. 194-205. https://doi.org/10.1016/j.cmpb.2014.01.009
Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images
Sharif, M., Qahwaji, R., Ipson, S. and Brahma, A. 2015. Medical image classification based on artificial intelligence approaches: A practical study on normal and abnormal confocal corneal images. Applied Soft Computing. 36 (Nov.), pp. 269-282. https://doi.org/10.1016/j.asoc.2015.07.019
An efficient intelligent analysis system for confocal corneal endothelium images
Sharif, M., Qahwaji, R., Shahamatnia, E., Alzubaidi, R., Ipson, S. and Brahma, A. 2015. An efficient intelligent analysis system for confocal corneal endothelium images. Computer Methods and Programs in Biomedicine. 122 (3), pp. 421-436. https://doi.org/10.1016/j.cmpb.2015.09.003
In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study
Alzubaidi, Rania, Sharif, M., Qahwaji, Rami, Ipson, Stanley and Brahma, Arun 2015. In Vivo Confocal Microscopic Corneal Images in health and disease with an emphasis on extracting features and visual signatures for corneal diseases: A review study. British Journal of Ophthalmology. 100 (1), pp. 41-55. https://doi.org/10.1136/bjophthalmol-2015-306934
A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing
Pizzamiglio, S., Naeem, U., ur Réhman, Shafiq, Sharif, M., Abdalla, H. and Turner, D. 2017. A Mutlimodal Approach to Measure the Levels Distraction of Pedestrians using Mobile Sensing. Procedia Computer Science. 113, pp. 89-96. https://doi.org/10.1016/j.procs.2017.08.297
Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample
Sankar, Anjali, Zhang, Tianhao, Gaonkar, Bilwaj, Doshi, Jimit, Erus, Guray, Costafreda, Sergi G., Marangell, Lauren, Davatzikos, Christos and Fu, C. 2016. Diagnostic potential of structural neuroimaging for depression from a multi-ethnic community sample. BJPsych Open. 2 (4), pp. 247-254. https://doi.org/10.1192/bjpo.bp.115.002493
Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes
Moulton, Calum D., Costafreda, Sergi G., Horton, Paul, Ismail, Khalida and Fu, C. 2015. Meta-analyses of structural regional cerebral effects in type 1 and type 2 diabetes. Brain Imaging and Behavior. 9 (4), pp. 651-662.
A systematic review of the neurophysiology of mindfulness on EEG oscillations
Lomas, T., Ivtzan, I. and Fu, C. 2015. A systematic review of the neurophysiology of mindfulness on EEG oscillations. Neuroscience & Biobehavioral Reviews. 57, pp. 401-410.
Multimodal functional and structural neuroimaging investigation of major depressive disorder following treatment with duloxetine
Fu, C., Costafreda, Sergi G, Sankar, Anjali, Adams, Tracey M, Rasenick, Mark M, Liu, Peng, Donati, Robert, Maglanoc, Luigi A, Horton, Paul and Marangell, Lauren B 2015. Multimodal functional and structural neuroimaging investigation of major depressive disorder following treatment with duloxetine. BMC Psychiatry. 15 (1).
Neural effects of cognitive–behavioural therapy on dysfunctional attitudes in depression
Sankar, A., Scott, J., Paszkiewicz, A., Giampietro, V. P., Steiner, H. and Fu, C. 2014. Neural effects of cognitive–behavioural therapy on dysfunctional attitudes in depression. Psychological Medicine. 45 (7), pp. 1425-1433.
Modulatory effects of brain-derived neurotrophic factor Val66Met polymorphism on prefrontal regions in major depressive disorder
Legge, R. M., Sendi, S., Cole, J. H., Cohen-Woods, S., Costafreda, S. G., Simmons, A., Farmer, A. E., Aitchison, K. J., McGuffin, P. and Fu, C. 2015. Modulatory effects of brain-derived neurotrophic factor Val66Met polymorphism on prefrontal regions in major depressive disorder. The British Journal of Psychiatry. 206 (5), pp. 379-384.
Prognostic and Diagnostic Potential of the Structural Neuroanatomy of Depression
Domschke, Katharina, Costafreda, Sergi G., Chu, Carlton, Ashburner, John and Fu, C. 2009. Prognostic and Diagnostic Potential of the Structural Neuroanatomy of Depression. PLoS ONE. 4 (7), p. e6353.
Pattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorder
Costafreda, Sergi G, Fu, C., Picchioni, Marco, Toulopoulou, Timothea, McDonald, Colm, Kravariti, Eugenia, Walshe, Muriel, Prata, Diana, Murray, Robin M and McGuire, Philip K 2011. Pattern of neural responses to verbal fluency shows diagnostic specificity for schizophrenia and bipolar disorder. BMC Psychiatry. 11 (1), p. 18.
Neuroimaging-Based Biomarkers in Psychiatry: Clinical Opportunities of a Paradigm Shift
Fu, C. and Costafreda, Sergi G. 2013. Neuroimaging-Based Biomarkers in Psychiatry: Clinical Opportunities of a Paradigm Shift. Canadian Journal of Psychiatry. 58 (9), pp. 499-508.