| The use of receiver operating characteristic curves in biomedical informatics TA Lasko, JG Bhagwat, KH Zou, L Ohno-Machado Journal of biomedical informatics 38 (5), 404-415, 2005 | 1089 | 2005 |
| Computational phenotype discovery using unsupervised feature learning over noisy, sparse, and irregular clinical data TA Lasko, JC Denny, MA Levy PloS one 8 (6), e66341, 2013 | 387 | 2013 |
| Calibration drift in regression and machine learning models for acute kidney injury SE Davis, TA Lasko, G Chen, ED Siew, ME Matheny Journal of the American Medical Informatics Association 24 (6), 1052-1061, 2017 | 282 | 2017 |
| Portability of an algorithm to identify rheumatoid arthritis in electronic health records RJ Carroll, WK Thompson, AE Eyler, AM Mandelin, T Cai, RM Zink, ... Journal of the American Medical Informatics Association 19 (e1), e162-e169, 2012 | 251 | 2012 |
| A study of active learning methods for named entity recognition in clinical text Y Chen, TA Lasko, Q Mei, JC Denny, H Xu Journal of biomedical informatics 58, 11-18, 2015 | 200 | 2015 |
| Development and evaluation of an ensemble resource linking medications to their indications WQ Wei, RM Cronin, H Xu, TA Lasko, L Bastarache, JC Denny Journal of the American Medical Informatics Association 20 (5), 954-961, 2013 | 126 | 2013 |
| Evaluating electronic health record data sources and algorithmic approaches to identify hypertensive individuals PL Teixeira, WQ Wei, RM Cronin, H Mo, JP VanHouten, RJ Carroll, ... Journal of the American Medical Informatics Association 24 (1), 162-171, 2016 | 106 | 2016 |
| A nonparametric updating method to correct clinical prediction model drift SE Davis, RA Greevy Jr, C Fonnesbeck, TA Lasko, CG Walsh, ... Journal of the American Medical Informatics Association 26 (12), 1448-1457, 2019 | 101 | 2019 |
| Melatonin suppression by illumination of upper and lower visual fields TA Lasko, DF Kripke, JA Elliot Journal of biological rhythms 14 (2), 122-125, 1999 | 97 | 1999 |
| Detection of calibration drift in clinical prediction models to inform model updating SE Davis, RA Greevy Jr, TA Lasko, CG Walsh, ME Matheny Journal of Biomedical Informatics 112, 103611, 2020 | 87 | 2020 |
| Predicting changes in hypertension control using electronic health records from a chronic disease management program J Sun, CD McNaughton, P Zhang, A Perer, A Gkoulalas-Divanis, ... Journal of the American Medical Informatics Association 21 (2), 337-344, 2013 | 86 | 2013 |
| Predicting medications from diagnostic codes with recurrent neural networks JM Bajor, TA Lasko International conference on learning representations, 2016 | 70 | 2016 |
| UNesT: local spatial representation learning with hierarchical transformer for efficient medical segmentation X Yu, Q Yang, Y Zhou, LY Cai, R Gao, HH Lee, T Li, S Bao, Z Xu, ... Medical Image Analysis 90, 102939, 2023 | 65 | 2023 |
| Is this “my” patient? Development and validation of a predictive model to link patients to primary care providers SJ Atlas, Y Chang, TA Lasko, HC Chueh, RW Grant, MJ Barry Journal of general internal medicine 21 (9), 973-978, 2006 | 65 | 2006 |
| Efficient inference of Gaussian-process-modulated renewal processes with application to medical event data TA Lasko Uncertainty in artificial intelligence: proceedings of the... conference …, 2014 | 60 | 2014 |
| Demystifying artificial intelligence in pharmacy SD Nelson, CG Walsh, CA Olsen, AJ McLaughlin, JR LeGrand, N Schutz, ... American Journal of Health-System Pharmacy 77 (19), 1556-1570, 2020 | 59 | 2020 |
| SynTEG: a framework for temporal structured electronic health data simulation Z Zhang, C Yan, TA Lasko, J Sun, BA Malin Journal of the American Medical Informatics Association 28 (3), 596-604, 2021 | 58 | 2021 |
| Machine Learning for Risk Prediction of Acute Coronary Syndrome JP VanHouten, JM Starmer, NM Lorenzi, DJ Maron, TA Lasko AMIA Annual Symposium Proceedings 2014, 1940, 2014 | 54 | 2014 |
| Calibration Drift Among Regression and Machine Learning Models for Hospital Mortality SE Davis, TA Lasko, G Chen, ME Matheny AMIA Annual Symposium Proceedings 2017, 625, 2017 | 53 | 2017 |
| Fully automatic liver attenuation estimation combing CNN segmentation and morphological operations Y Huo, JG Terry, J Wang, S Nair, TA Lasko, BI Freedman, JJ Carr, ... Medical physics 46 (8), 3508-3519, 2019 | 45 | 2019 |
