| Heart disease classification using data mining tools and machine learning techniques I Tougui, A Jilbab, J El Mhamdi Health and Technology 10 (5), 1137-1144, 2020 | 128 | 2020 |
| Discriminating between patients with Parkinson’s and neurological diseases using cepstral analysis A Benba, A Jilbab, A Hammouch IEEE transactions on neural systems and rehabilitation engineering 24 (10 …, 2016 | 105 | 2016 |
| Voiceprints analysis using MFCC and SVM for detecting patients with Parkinson's disease A Benba, A Jilbab, A Hammouch, S Sandabad 2015 International conference on electrical and information technologies …, 2015 | 97 | 2015 |
| Comparing CT scan and chest X-ray imaging for COVID-19 diagnosis E Benmalek, J Elmhamdi, A Jilbab Biomedical Engineering Advances 1, 100003, 2021 | 88 | 2021 |
| Wireless sensor networks in biomedical: Wireless body area networks B Abidi, A Jilbab, MEL Haziti Europe and MENA cooperation advances in information and communication …, 2017 | 80 | 2017 |
| Impact of the choice of cross-validation techniques on the results of machine learning-based diagnostic applications I Tougui, A Jilbab, J El Mhamdi Healthcare informatics research 27 (3), 189-199, 2021 | 79 | 2021 |
| Analysis of multiple types of voice recordings in cepstral domain using MFCC for discriminating between patients with Parkinson’s disease and healthy people A Benba, A Jilbab, A Hammouch International Journal of Speech Technology 19, 449-456, 2016 | 76 | 2016 |
| Detecting patients with Parkinson's disease using Mel frequency cepstral coefficients and support vector machines A Benba, A Jilbab, A Hammouch International Journal on Electrical Engineering and Informatics 7 (2), 297, 2015 | 59 | 2015 |
| Wireless body area networks: a comprehensive survey B Abidi, A Jilbab, EH Mohamed Journal of medical engineering & technology 44 (3), 97-107, 2020 | 55 | 2020 |
| Using human factor cepstral coefficient on multiple types of voice recordings for detecting patients with Parkinson's disease A Benba, A Jilbab, A Hammouch Irbm 38 (6), 346-351, 2017 | 50 | 2017 |
| Voice analysis for detecting persons with Parkinson’s disease using MFCC and VQ A Benba, A Jilbab, A Hammouch The 2014 international conference on circuits, systems and signal processing …, 2014 | 39 | 2014 |
| Phonocardiogram signals processing approach for PASCAL classifying heart sounds challenge F Chakir, A Jilbab, C Nacir, A Hammouch Signal, Image and Video Processing 12, 1149-1155, 2018 | 37 | 2018 |
| An energy efficiency routing protocol for wireless body area networks B Abidi, A Jilbab, EH Mohamed Journal of medical engineering & technology 42 (4), 290-297, 2018 | 36 | 2018 |
| Comparison of classification methods to detect the Parkinson disease A Bourouhou, A Jilbab, C Nacir, A Hammouch 2016 international conference on electrical and information technologies …, 2016 | 35 | 2016 |
| Hybridization of best acoustic cues for detecting persons with Parkinson's disease A Benba, A Jilbab, A Hammouch 2014 Second World Conference on Complex Systems (WCCS), 622-625, 2014 | 35 | 2014 |
| Multiclass classification of Parkinson’s disease using different classifiers and LLBFS feature selection algorithm E Benmalek, J Elmhamdi, A Jilbab International Journal of Speech Technology 20, 179-184, 2017 | 33 | 2017 |
| Voice assessments for detecting patients with Parkinson’s diseases using PCA and NPCA A Benba, A Jilbab, A Hammouch International Journal of Speech Technology 19, 743-754, 2016 | 31 | 2016 |
| Wearable wireless sensors network for ECG telemonitoring using neural network for features extraction A El Attaoui, M Hazmi, A Jilbab, A Bourouhou Wireless Personal Communications 111 (3), 1955-1976, 2020 | 30 | 2020 |
| Wireless body area network for health monitoring B Abidi, A Jilbab, EH Mohamed Journal of medical engineering & technology 43 (2), 124-132, 2019 | 29 | 2019 |
| A health remote monitoring application based on wireless body area networks E Baba, A Jilbab, A Hammouch 2018 International Conference on Intelligent Systems and Computer Vision …, 2018 | 29 | 2018 |
