| Prediction of preterm deliveries from EHG signals using machine learning P Fergus, P Cheung, A Hussain, D Al-Jumeily, C Dobbins, S Iram PloS one 8 (10), e77154, 2013 | 169 | 2013 |
| Automatic epileptic seizure detection using scalp EEG and advanced artificial intelligence techniques P Fergus, D Hignett, A Hussain, D Al-Jumeily, K Abdel-Aziz BioMed research international 2015, 2015 | 144 | 2015 |
| A machine learning system for automated whole-brain seizure detection P Fergus, A Hussain, D Hignett, D Al-Jumeily, K Abdel-Aziz, H Hamdan Applied Computing and Informatics 12 (1), 70-89, 2016 | 132 | 2016 |
| A first implementation of underwater communications in raw water using the 433 MHz frequency combined with a bowtie antenna S Ryecroft, A Shaw, P Fergus, P Kot, K Hashim, A Moody, L Conway Sensors 19 (8), 1813, 2019 | 93 | 2019 |
| Advanced artificial neural network classification for detecting preterm births using EHG records P Fergus, I Idowu, A Hussain, C Dobbins Neurocomputing 188, 42-49, 2016 | 86 | 2016 |
| A novel gesomin detection method based on microwave spectroscopy SP Ryecroft, A Shaw, P Fergus, P Kot, K Hashim, L Conway, A Moody 2019 12th International Conference on Developments in eSystems Engineering …, 2019 | 71 | 2019 |
| Dynamic neural network architecture inspired by the immune algorithm to predict preterm deliveries in pregnant women AJ Hussain, P Fergus, H Al-Askar, D Al-Jumeily, F Jager Neurocomputing 151, 963-974, 2015 | 64 | 2015 |
| Machine learning Ensemble Modelling to classify caesarean section and vaginal delivery types using cardiotocography traces P Fergus, S Malarvizhi, C Chalmers Computers in Biology and Medicine 93 (February), 7-16, 2018 | 62 | 2018 |
| Predicting the likelihood of heart failure with a multi level risk assessment using decision tree AJ Aljaaf, D Al-Jumeily, AJ Hussain, T Dawson, P Fergus, M Al-Jumaily 2015 Third International Conference on Technological Advances in Electrical …, 2015 | 61 | 2015 |
| Managing distributed networked appliances in home networks M Merabti, P Fergus, O Abuelma'atti, H Yu, C Judice Proceedings of the IEEE 96 (1), 166-185, 2008 | 61 | 2008 |
| A novel method of early diagnosis of Alzheimer’s disease based on EEG signals D Al-Jumeily, S Iram, FB Vialatte, P Fergus, A Hussain The scientific world journal 2015, 2015 | 54 | 2015 |
| Classification of caesarean section and normal vaginal deliveries using foetal heart rate signals and advanced machine learning algorithms P Fergus, A Hussain, D Al-Jumeily, DS Huang, N Bouguila Biomedical engineering online 16 (1), 1-26, 2017 | 51 | 2017 |
| Body area networks for movement analysis in physiotherapy treatments K Kifayat, P Fergus, S Cooper, M Merabti 2010 IEEE 24th International Conference on Advanced Information Networking …, 2010 | 44 | 2010 |
| Deep learning classification of polygenic obesity using genome wide association study SNPs CAC Montaez, P Fergus, AC Montaez, A Hussain, D Al-Jumeily, ... 2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018 | 41 | 2018 |
| Utilising Deep Learning and Genome Wide Association Studies for Epistatic-Driven Preterm Birth Classification in African-American Women P Fergus, A Montanez, B Abdulaimma, P Lisboa, C Chalmers, B Pineles IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2018 | 40 | 2018 |
| Machine learning approaches for the prediction of obesity using publicly available genetic profiles CAC Montañez, P Fergus, A Hussain, D Al-Jumeily, B Abdulaimma, ... 2017 International Joint Conference on Neural Networks (IJCNN), 2743-2750, 2017 | 39 | 2017 |
| Toward an optimal use of artificial intelligence techniques within a clinical decision support system AJ Aljaaf, D Al-Jumeily, AJ Hussain, P Fergus, M Al-Jumaily, K Abdel-Aziz 2015 Science and Information Conference (SAI), 548-554, 2015 | 38 | 2015 |
| Sccir: Smart cities critical infrastructure response framework A Attwood, M Merabti, P Fergus, O Abuelmaatti 2011 Developments in E-systems Engineering, 460-464, 2011 | 38 | 2011 |
| Machine learning approaches to the application of disease modifying therapy for sickle cell using classification models M Khalaf, AJ Hussain, R Keight, D Al-Jumeily, P Fergus, R Keenan, P Tso Neurocomputing 228, 154-164, 2017 | 37 | 2017 |
| Dynamic service composition in home appliance networks A Mingkhwan, P Fergus, O Abuelma’atti, M Merabti, B Askwith, ... Multimedia Tools and Applications 29, 257-284, 2006 | 37 | 2006 |
Carl ChalmersLiverpool John Moores UniversityVerified email at ljmu.ac.uk
