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

Book chapter

van Druten, J., Sharif, M., Khashu, M. and Abdalla, H. 2019. A Proposed Machine Learning Based Collective Disease Model to Enable Predictive Diagnostics in Necrotising Enterocolitis. in: Miraz, M. H., Excell, P. S., Jones, A., Soomro, S. and Ali, M. (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 101-106
Authorsvan Druten, J., Sharif, M., Khashu, M. and Abdalla, H.
EditorsMiraz, M. H., Excell, P. S., Jones, A., Soomro, S. and Ali, M.
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
Submitted17 Jun 2018
Deposited10 Aug 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
Copyright holder© 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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Assadi Langroudi, A., Abdalla, H. and Ghadr, S. 2022. Fractals for the Sustainable Design of Engineered Particulate Systems. Sustainability. 14 (Art. 7287). https://doi.org/10.3390/su14127287
Potential of Connected Fully Autonomous Vehicles in Reducing Congestion and Associated Carbon Emissions
Neufville, R., Abdalla, H. and Abbas, A. 2022. Potential of Connected Fully Autonomous Vehicles in Reducing Congestion and Associated Carbon Emissions. Sustainability. 14 (Art. 6910). https://doi.org/10.3390/su14116910
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
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
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
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
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
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
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
A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser
Alsallal, M., Sharif, M., Al-Ghzawi, B. and al Mutoki, S. M. M. 2019. A Machine Learning Techniques to Detect Counterfeit Medicine Based on X-Ray Fluorescence Analyser. in: Miraz, M. H., Excell, P. S., Jones, A., Soomro, S. and Ali, M. (ed.) Proceedings 2018 International Conference on Computing, Electronics & Communications Engineering (iCCECE) IEEE. pp. 118-122
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
Neural Predictors of Gait Stability When Walking Freely in the Real-World.
Pizzamiglio, S., Abdalla, H., Naeem, U. and Turner, D. 2018. Neural Predictors of Gait Stability When Walking Freely in the Real-World. Journal of NeuroEngineering and Rehabilitation. 15 (11). https://doi.org/10.1186/s12984-018-0357-z
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
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
Energy Saving of the Domestic Housing Stocks: Application Development as a Plug-In for Energy Simulation Software
Shi, W., Abdalla, H., Elsharkawy, Heba and Chandler, A. 2017. Energy Saving of the Domestic Housing Stocks: Application Development as a Plug-In for Energy Simulation Software. International Journal of Parallel, Emergent and Distributed Systems. 32 (Sup 1), pp. S114-S132. https://doi.org/10.1080/17445760.2017.1390104
Investigation Into ERP-Based Symbiotic Simulation Project Implentation On Ford Engine Production Line: Challenges, Opportunities and Prospects
Chiroma, Emmanuel, Ladbrook, John and Abdalla, H. 2016. Investigation Into ERP-Based Symbiotic Simulation Project Implentation On Ford Engine Production Line: Challenges, Opportunities and Prospects. in: Bruzzone, Agostino G., De Felice, Fabio, Frydman, Claudia, Massei, Marina, Merkuryev, Yuri and Solis, Adriano (ed.) Proceedings of the International Conference on Modelling and Applied Simulation 2016 DIME Università Di Genova. pp. 57-64
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
Neural correlates of single- and dual-task walking in the real world
Pizzamiglio, Sara, Naeem, U., Abdalla, H. and Turner, D. 2017. Neural correlates of single- and dual-task walking in the real world. Frontiers in Human Neuroscience. 11, p. Art 460. https://doi.org/10.3389/fnhum.2017.00460
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.
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