| 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 | 192 | 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 (1), 986736, 2015 | 182 | 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 | 175 | 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 | 99 | 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 | 96 | 2016 |
| 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 | 80 | 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 | 80 | 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, 1-26, 2017 | 73 | 2017 |
| 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 | 71 | 2015 |
| 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 | 64 | 2019 |
| 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 | 62 | 2017 |
| 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 (1), 931387, 2015 | 59 | 2015 |
| 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 | 54 | 2015 |
| Detecting activities of daily living and routine behaviours in dementia patients living alone using smart meter load disaggregation C Chalmers, P Fergus, CAC Montanez, S Sikdar, F Ball, B Kendall IEEE Transactions on Emerging Topics in Computing 10 (1), 157-169, 2020 | 53 | 2020 |
| 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 | 53 | 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 | 50 | 2018 |
| Artificial intelligence for detecting preterm uterine activity in gynecology and obstetric care IO Idowu, P Fergus, A Hussain, C Dobbins, M Khalaf, RVC Eslava, ... 2015 IEEE international conference on computer and information technology …, 2015 | 49 | 2015 |
| 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 | 47 | 2017 |
| An evaluation of platforms for processing camera‐trap data using artificial intelligence J Vélez, W McShea, H Shamon, PJ Castiblanco‐Camacho, MA Tabak, ... Methods in Ecology and Evolution 14 (2), 459-477, 2023 | 45 | 2023 |
Carl ChalmersLiverpool John Moores UniversityVerified email at ljmu.ac.uk
