| Efficient treatment of outliers and class imbalance for diabetes prediction N Nnamoko, I Korkontzelos Artificial intelligence in medicine 104, 101815, 2020 | 122 | 2020 |
| Evaluation of filter and wrapper methods for feature selection in supervised machine learning N Nnamoko, F Arshad, D England, J Vora, J Norman Age 21 (81), 33-2, 2014 | 57 | 2014 |
| Predicting diabetes onset: an ensemble supervised learning approach N Nnamoko, A Hussain, D England 2018 IEEE Congress on evolutionary computation (CEC), 1-7, 2018 | 55 | 2018 |
| Fuzzy expert system for Type 2 Diabetes Mellitus (T2DM) management using dual inference mechanism NA Nnamoko, F Arshad, D England, J Vora 2013 AAAI Spring Symposium Series, 2013 | 26 | 2013 |
| Telehealth in Primary Health Care: Analysis of Liverpool NHS Experience D Al-Jumeily, A Hussain, C Mallucci, C Oliver Morgan Kaufmann, 2015 | 24* | 2015 |
| Solid waste image classification using deep convolutional neural network N Nnamoko, J Barrowclough, J Procter Infrastructures 7 (4), 47, 2022 | 23 | 2022 |
| Patient-reported outcome measures: an on-line system empowering patient choice J Wilson, F Arshad, N Nnamoko, A Whiteman, J Ring, B Roy Journal of the American Medical Informatics Association 21 (4), 725-729, 2014 | 16 | 2014 |
| Gender prediction with descriptive textual data using a Machine Learning approach B Onikoyi, N Nnamoko, I Korkontzelos Natural Language Processing Journal 4, 100018, 2023 | 14 | 2023 |
| Classification techniques using EHG signals for detecting preterm births IO Idowu PQDT-UK & Ireland, 2017 | 13 | 2017 |
| A threshold genetic algorithm for diagnosis of diabetes using minkowski distance method E Sreedevi, MA Padmavathamma International Journal of Innovative Research in Science, Engineering and …, 2015 | 11 | 2015 |
| Meta-classification model for diabetes onset forecast: A proof of concept NA Nnamoko, FN Arshad, D England, J Vora 2014 IEEE International Conference on Bioinformatics and Biomedicine (BIBM …, 2014 | 11 | 2014 |
| Bug severity prediction using a hierarchical one-vs.-remainder approach N Nnamoko, LA Cabrera-Diego, D Campbell, Y Korkontzelos Natural Language Processing and Information Systems: 24th International …, 2019 | 8 | 2019 |
| Improving healthcare system usability without real users: A semi-parallel design approach F Arshad, N Nnamoko, J Wilson, B Roy, M Taylor International Journal of Healthcare Information Systems and Informatics …, 2015 | 7 | 2015 |
| Fuzzy inference model for type 2 diabetes management: a tool for regimen alterations N Nnamoko, F Arshad, D England, J Vora, J Norman Journal of Computer Sciences and Applications 3 (3A), 40-45, 2015 | 6 | 2015 |
| Personalised accelerometer cut-point prediction for older adults’ movement behaviours using a machine learning approach N Nnamoko, LA Cabrera-Diego, D Campbell, G Sanders, SJ Fairclough, ... Computer Methods and Programs in Biomedicine 208, 106165, 2021 | 5 | 2021 |
| A behaviour biometrics dataset for user identification and authentication N Nnamoko, J Barrowclough, M Liptrott, I Korkontzelos Data in Brief 45, 108728, 2022 | 3 | 2022 |
| CyberSignature: A user authentication tool based on behavioural biometrics N Nnamoko, I Korkontzelos, J Barrowclough, M Liptrott Software Impacts 14, 100443, 2022 | 2 | 2022 |
| Waste Classification Dataset N Nnamoko, J Barrowclough, J Procter Mendeley Data, 2022 | 2 | 2022 |
| Ensemble-based Supervised Learning for Predicting Diabetes Onset NA Nnamoko PQDT-Global, 2018 | 1 | 2018 |
| Quantitative metrics to the CARS model in academic discourse in biology introductions C Lam, N Nnamoko Proceedings of the 5th Workshop on Computational Approaches to Discourse …, 2024 | | 2024 |
Ioannis KorkontzelosProfessor in Computer Science (Data Analytics), Department of Computer Science, Edge Hill UniversityVerified email at edgehill.ac.uk
