| Artificial intelligence and machine learning approaches using gene expression and variant data for personalized medicine S Vadapalli, H Abdelhalim, S Zeeshan, Z Ahmed Briefings in bioinformatics 23 (5), bbac191, 2022 | 41 | 2022 |
| Artificial intelligence, healthcare, clinical genomics, and pharmacogenomics approaches in precision medicine H Abdelhalim, A Berber, M Lodi, R Jain, A Nair, A Pappu, K Patel, ... Frontiers in genetics 13, 929736, 2022 | 34 | 2022 |
| Investigating genes associated with heart failure, atrial fibrillation, and other cardiovascular diseases, and predicting disease using machine learning techniques for … V Venkat, H Abdelhalim, W DeGroat, S Zeeshan, Z Ahmed Genomics 115 (2), 110584, 2023 | 17 | 2023 |
| Genomic approaches to identify and investigate genes associated with atrial fibrillation and heart failure susceptibility KK Patel, C Venkatesan, H Abdelhalim, S Zeeshan, Y Arima, ... Human genomics 17 (1), 47, 2023 | 11 | 2023 |
| Discovering biomarkers associated and predicting cardiovascular disease with high accuracy using a novel nexus of machine learning techniques for precision medicine W DeGroat, H Abdelhalim, K Patel, D Mendhe, S Zeeshan, Z Ahmed Scientific reports 14 (1), 1, 2024 | 9 | 2024 |
| Hygieia: AI/ML pipeline integrating healthcare and genomics data to investigate genes associated with targeted disorders and predict disease W DeGroat, V Venkat, W Pierre-Louis, H Abdelhalim, Z Ahmed Software Impacts 16, 100493, 2023 | 6 | 2023 |
| IntelliGenes: a novel machine learning pipeline for biomarker discovery and predictive analysis using multi-genomic profiles W DeGroat, D Mendhe, A Bhusari, H Abdelhalim, S Zeeshan, Z Ahmed Bioinformatics 39 (12), btad755, 2023 | 3 | 2023 |
| Functional mutation, splice, distribution, and divergence analysis of impactful genes associated with heart failure and other cardiovascular diseases I Mhatre, H Abdelhalim, W Degroat, S Ashok, BT Liang, Z Ahmed Scientific reports 13 (1), 16769, 2023 | 3 | 2023 |
| RNA‐seq‐driven expression analysis to investigate cardiovascular disease genes with associated phenotypes among atrial fibrillation patients A Berber, H Abdelhalim, S Zeeshan, S Vadapalli, B von Oehsen, ... Clinical and translational medicine 12 (7), 2022 | 3 | 2022 |
| Investigating genes associated with cardiovascular disease among heart failure patients for translational research and precision medicine Z Ahmed, S Zeeshan, N Persaud, W Degroat, H Abdelhalim, BT Liang Clinical and translational discovery 3 (3), e206, 2023 | 2 | 2023 |
| Deciphering genomic signatures associating human dental oral craniofacial diseases with cardiovascular diseases using machine learning approaches Z Ahmed, W Degroat, H Abdelhalim, S Zeeshan, D Fine Clinical oral investigations 28 (1), 52, 2024 | 1 | 2024 |
| GWAS advancements to investigate disease associations and biological mechanisms O Omidiran, A Patel, S Usman, I Mhatre, H Abdelhalim, W DeGroat, ... Clinical and Translational Discovery 4 (3), e296, 2024 | | 2024 |
| Role of genome-wide association studies, polygenic risk score and AI/ML using big data for personalized treatment to the patients with cardiovascular disease H Abdelhalim, RM Hunter, W DeGroat, D Mendhe, S Zeeshan, Z Ahmed Future Medicine AI, FMAI10, 2023 | | 2023 |
| Integrated ACMG-approved genes and ICD codes for the translational research and precision medicine R Wable, AS Nair, A Pappu, W Pierre-Louis, H Abdelhalim, K Patel, ... Database 2023, baad033, 2023 | | 2023 |
| Identification of Anti-Inflammatory Compounds Present in Nigella Sativa and Analyzing Their Effects on the Inflammation Pathway Using In Silico Techniques H Abdelhalim, S Arora Aresty Rutgers Undergraduate Research Journal 1 (4), 2022 | | 2022 |
