| Machine learning in health care and laboratory medicine: General overview of supervised learning and Auto‐ML HH Rashidi, N Tran, S Albahra, LT Dang International Journal of Laboratory Hematology 43, 15-22, 2021 | 52 | 2021 |
| Evolving applications of artificial intelligence and machine learning in infectious diseases testing NK Tran, S Albahra, L May, S Waldman, S Crabtree, S Bainbridge, ... Clinical chemistry 68 (1), 125-133, 2022 | 45 | 2022 |
| Artificial intelligence and machine learning overview in pathology & laboratory medicine: A general review of data preprocessing and basic supervised concepts S Albahra, T Gorbett, S Robertson, G D'Aleo, SVS Kumar, S Ockunzzi, ... Seminars in Diagnostic Pathology 40 (2), 71-87, 2023 | 38 | 2023 |
| Novel application of an automated-machine learning development tool for predicting burn sepsis: proof of concept NK Tran, S Albahra, TN Pham, JH Holmes IV, D Greenhalgh, TL Palmieri, ... Scientific reports 10 (1), 12354, 2020 | 38 | 2020 |
| Automated en masse machine learning model generation shows comparable performance as classic regression models for predicting delayed graft function in renal allografts KY Jen, S Albahra, F Yen, J Sageshima, LX Chen, N Tran, HH Rashidi Transplantation 105 (12), 2646-2654, 2021 | 14 | 2021 |
| Innovations in infectious disease testing: leveraging COVID-19 pandemic technologies for the future NK Tran, S Albahra, H Rashidi, L May Clinical Biochemistry 117, 10-15, 2023 | 13 | 2023 |
| Common statistical concepts in the supervised Machine Learning arena HH Rashidi, S Albahra, S Robertson, NK Tran, B Hu Frontiers in Oncology 13, 1130229, 2023 | 12 | 2023 |
| Enhancing military burn-and trauma-related acute kidney injury prediction through an automated machine learning platform and point-of-care testing HH Rashidi, A Makley, TL Palmieri, S Albahra, J Loegering, L Fang, ... Archives of Pathology & Laboratory Medicine 145 (3), 320-326, 2021 | 11 | 2021 |
| Comparative performance of two automated machine learning platforms for COVID-19 detection by MALDI-TOF-MS HH Rashidi, J Pepper, T Howard, K Klein, L May, S Albahra, B Phinney, ... PloS one 17 (7), e0263954, 2022 | 7 | 2022 |
| Prediction of tuberculosis using an automated machine learning platform for models trained on synthetic data HH Rashidi, IH Khan, LT Dang, S Albahra, U Ratan, N Chadderwala, ... Journal of pathology informatics 13, 100172, 2022 | 7 | 2022 |
| The ChatGPT conundrum: Human-generated scientific manuscripts misidentified as AI creations by AI text detection tool HH Rashidi, BD Fennell, S Albahra, B Hu, T Gorbett Journal of Pathology Informatics 14, 100342, 2023 | 6 | 2023 |
| Systems and methods for automated machine learning HH Rashidi, S Albahra, N Tran US Patent App. 17/100,082, 2021 | 4 | 2021 |
| Automated machine learning for endemic active tuberculosis prediction from multiplex serological data HH Rashidi, LT Dang, S Albahra, R Ravindran, IH Khan Scientific reports 11 (1), 17900, 2021 | 3 | 2021 |
| STNG (Synthetic Tabular Neural Generator): A Novel and Fully Automated Platform for Synthetic Tabular Data Generation and Validation H Rashidi, S Albahra, B Rubin, B Hu | | 2023 |
| COMPARATIVE PERFORMANCE OF TWO AUTOMATED MACHINE LEARNING PLATFORMS FOR COVID-19 DETECTION BY MALDI-TOF-MS (preprint) HH Rashidi, J Pepper, T Howard, K Klein, L May, S Albahra, B Phinney, ... | | 2022 |
| Archived Past Lab Bests Real N Tran, S Albahra | | |
| Archived Past Lab Best Practice R Thomas, S Albahra, CLS Scott Bainbridge, NK Tran | | |
| Lab Best Practice R Thomas, S Barnhard | | |
Bo HuCleveland Clinic, Case Western Reserve UniversityVerified email at case.edu
