| Blood glucose level prediction: advanced deep-ensemble learning approach H Nemat, H Khadem, MR Eissa, J Elliott, M Benaissa IEEE journal of biomedical and health informatics 26 (6), 2758-2769, 2022 | 55 | 2022 |
| Classification of breast lesions in ultrasonography using sparse logistic regression and morphology‐based texture features H Nemat, H Fehri, N Ahmadinejad, AF Frangi, A Gooya Medical physics 45 (9), 4112-4124, 2018 | 36 | 2018 |
| COVID-19 mortality risk assessments for individuals with and without diabetes mellitus: Machine learning models integrated with interpretation framework H Khadem, H Nemat, MR Eissa, J Elliott, M Benaissa Computers in Biology and Medicine 144, 105361, 2022 | 20 | 2022 |
| Classification before regression for improving the accuracy of glucose quantification using absorption spectroscopy H Khadem, MR Eissa, H Nemat, O Alrezj, M Benaissa Talanta 211, 120740, 2020 | 18 | 2020 |
| Multi-lag stacking for blood glucose level prediction H Khadem, H Nemat, J Elliott, M Benaissa Knowledge Discovery in Healthcare Data 2020 2675, 146-150, 2020 | 17 | 2020 |
| Data fusion of activity and CGM for predicting blood glucose levels H Nemat, H Khadem, J Elliott, M Benaissa Knowledge Discovery in Healthcare Data 2020 2675, 120-124, 2020 | 17 | 2020 |
| Blood glucose level time series forecasting: Nested deep ensemble learning lag fusion H Khadem, H Nemat, J Elliott, M Benaissa Bioengineering 10 (4), 487, 2023 | 15 | 2023 |
| Interpretable machine learning for inpatient covid-19 mortality risk assessments: Diabetes mellitus exclusive interplay H Khadem, H Nemat, J Elliott, M Benaissa Sensors 22 (22), 8757, 2022 | 12 | 2022 |
| Causality analysis in type 1 diabetes mellitus with application to blood glucose level prediction H Nemat, H Khadem, J Elliott, M Benaissa Computers in Biology and Medicine 153, 106535, 2023 | 10 | 2023 |
| Signal fragmentation based feature vector generation in a model agnostic framework with application to glucose quantification using absorption spectroscopy H Khadem, H Nemat, J Elliott, M Benaissa Talanta 243, 123379, 2022 | 10 | 2022 |
| In vitro glucose measurement from NIR and MIR spectroscopy: Comprehensive benchmark of machine learning and filtering chemometrics H Khadem, H Nemat, J Elliott, M Benaissa Heliyon 10 (10), 2024 | 2 | 2024 |
| Artificial intelligence in blood glucose level prediction for type 1 diabetes management H Nemat University of Sheffield, 2023 | 2 | 2023 |
| Data-driven blood glucose level prediction in type 1 diabetes: a comprehensive comparative analysis H Nemat, H Khadem, J Elliott, M Benaissa Scientific reports 14 (1), 21863, 2024 | 1 | 2024 |
| Clinical outcomes of a real‐world prospective study using Dexcom ONE continuous glucose monitoring in people with diabetes treated with two or more insulin injections per day J Elliott, C Husband, H Khadem, H Nemat, L Cardno, L Currin, S Hudson Diabetic Medicine, e15519, 2025 | | 2025 |
| Physical Activity Integration in Blood Glucose Level Prediction: Different Levels of Data Fusion H Nemat, H Khadem, J Elliott, M Benaissa IEEE Journal of Biomedical and Health Informatics, 2024 | | 2024 |
| Blood Glucose Level Time Series Forecasting: Nested Deep Ensemble Learning Lag Fusion. Bioengineering 2023, 10, 487 H Khadem, H Nemat, J Elliott, M Benaissa Health and Public Health Applications for Decision Support Using Machine …, 2023 | | 2023 |
| Classification of Benign and Malignant Tumors in Breast Ultrasound Images by using Morphological Features H Nemat, A Mahloojifar, A Gooya, N Ahmadinejad Journal of Machine Vision and Image Processing 4 (2), 75-89, 2017 | | 2017 |