A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis

Book chapter

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
Authorsvan Druten, Jacqueline, Sharif, M., Khashu, Minesh and Abdalla, H.
EditorsMiraz, Mahdi H., Exce, Peter S., Jones, Andrew, Soomro, Safeeullah and Ali, Maaruf
Abstract

Despite 60 years of research into necrotising
enterocolitis (NEC), our understanding of the disease has not
improved enough to achieve better outcomes. Even though
NEC has remained the leading cause of death and poor
outcomes in preterm infants, there remain vital questions on
how to define, differentiate and detect the condition. Numerous
international groups have recently highlighted NEC as a
research priority and called for broader engagement of the
scientific community to move the field forward. The three
foremost barriers at present are lack of suitable definition(s),
lack of clean datasets and consequently a lack of scope to gain
sufficient insights from data. This research paper proposes a
new direction of travel to advance neonatal gastro-intestinal
monitoring and strengthen our efforts to gain better insights
from global databases. An integrated machine learning based
model is recommended to produce a comprehensive disease
model to manage the complexity of this multi-variate disease.
This intelligent disease model would be used in the daily
neonatal settings to help aggregate data to support clinical
decision making, better capture the complexity of each patient
to enrich global datasets to create bigger and better data. This
paper reviews current machine learning and CAD technologies
in neonatology and suggests an innovative approach for an
NEC disease model.

Book titleProceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE)
Page range101-106
Year2019
PublisherIEEE
Publication dates
Print07 Mar 2019
Publication process dates
Deposited10 Aug 2018
Submitted17 Jun 2018
EventIEEE International Conference on Computing, Electronics & Communications Engineering 2018 (iCCECE '18)
ISBN978-1-5386-4904-6
978-1-5386-4903-9
978-1-5386-4905-3
Digital Object Identifier (DOI)https://doi.org/10.1109/iCCECOME.2018.8658948
Web address (URL)https://doi.org/10.1109/iCCECOME.2018.8658948
Additional information

© 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

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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.
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 Cost Effective and Light Weight Unipolar Electroadhesion Pad Technology for Adhesion Mechanism of Wall Climbing Robot
Yehya, Muhammd Irshad, Hussain, Salman, Wasim, Ahmad, Jahanza, Mirza and Abdalla, H. 2016. A Cost Effective and Light Weight Unipolar Electroadhesion Pad Technology for Adhesion Mechanism of Wall Climbing Robot. International Journal of Robotics and Mechatronics. 2 (1), pp. 1-10.
Predicting the tensile strength, impact toughness, and hardness of friction stir-welded AA6061-T6 using response surface methodology
Safeen, Wasif, Hussain, Salman, Wasim, Ahmad, Jahanzaib, Mirza, Aziz, Haris and Abdalla, H. 2016. Predicting the tensile strength, impact toughness, and hardness of friction stir-welded AA6061-T6 using response surface methodology. The International Journal of Advanced Manufacturing Technology. 87 (5-8), pp. 1765-1781. https://doi.org/10.1007/s00170-016-8565-9
An investigation into energy consumption behaviour and lifestyles in UK homes: Developing a smart application as a tool for reducing home energy use
Shi, W., Elsharkawy, H. and Abdalla, H. 2017. An investigation into energy consumption behaviour and lifestyles in UK homes: Developing a smart application as a tool for reducing home energy use. PLEA 2017: 33rd International Conference on Passive and Low Energy Architecture. Edinburgh, UK 03 - 05 Jul 2017 NCEUB.
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