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Dr. Shah’s research focuses on clinical applications of data science, machine learning, and natural language processing. Specifically, her current projects focus on: 1) phenotyping atrial fibrillation patients using natural language processing and big data analyses 2) predicting readmission after acute myocardial infarction with machine learning methods, incorporating socioeconomic status 3) predicting complications following cardiac surgery using neural networks, incorporating functional status derived using an ontology. The overall goal of Dr. Shah's work is to find the right treatments for the right patients, and maximize benefit while minimizing harm.
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medRxiv : the preprint server for health sciences (2023)
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2023 Computing in Cardiology (CinC) (2023): 1-4
The Journal of Heart and Lung Transplantationno. 9 (2022): 1228-1236
P. A. R. H. U. M. NAMDARAN, M. A. T. T. H. E. W. FINDLAY, J. E. F. F. GIBBS, E. L. I. Z. A. B. E. T. H. DRANOW,R. A. S. H. M. E. E. SHAH, S. T. A. V. R. O. S. DRAKOS,R. O. B. I. N. SHAW, J. A. M. E. S. FANG, K. E. V. I. N. SHAH
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Jeremiah R. Brown, Iben M. Ricket,Ruth M. Reeves,Rashmee U. Shah,Christine A. Goodrich, Glen Gobbel,Meagan E. Stabler,Amy M. Perkins,Freneka Minter,Kevin C. Cox,Chad Dorn,Jason Denton,
medRxivno. 1 (2022): e0000004
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