Dr. Suchi Saria

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Peter SchulamAmazon AlexaVerified email at amazon.com
Adarsh SubbaswamyU.S. Food and Drug AdministrationVerified email at fda.hhs.gov
Katharine HenryData Scientist at Janssen R&D | PhD Computer Science from Johns Hopkins UniversityVerified email at jhu.edu
Andong Zhan (展安东)Snowflake Inc.Verified email at snowflake.com
Daphne KollerCEO and Founder, insitroVerified email at insitro.com
David N. HagerAssociate Professor of Medicine, Johns Hopkins UniversityVerified email at jhmi.edu
David BatesProfessor of Medicine, Harvard Medical SchoolVerified email at partners.org
Roy AdamsJohns Hopkins UniversityVerified email at jhu.edu
Anna GoldenbergScientist, SickKids Research Institute; Assistant Professor Department of Computer Science, University of TorontoVerified email at utoronto.ca
E. Ray DorseyProfessor of Neurology, University of RochesterVerified email at chet.rochester.edu
Hossein SoleimaniUniversity of California, San FranciscoVerified email at ucsf.edu
Max A LittleUniversity of Birmingham/MITVerified email at mit.edu
Jenna WiensUniversity of MichiganVerified email at umich.edu
Isaac KohaneHarvard Medical School, Children's Hospital, Brigham and Women's HospitalVerified email at hms.harvard.edu
Lucila Ohno-MachadoUniversity of California San DiegoVerified email at ucsd.edu
Peter Pronovost, MD, PhDChief Clinical Transformation Officer University Hosptials ClevelandVerified email at uhhospitals.org
Finale Doshi-VelezProfessor, HarvardVerified email at seas.harvard.edu
Dr. Marzyeh GhassemiAssistant Professor, EECS.CSAIL/IMES, MITVerified email at mit.edu
Andreas TerzisGoogle DeepmindVerified email at google.com
Atul J. ButteDirector, Bakar Computational Health Sciences Institute, University of California, San FranciscoVerified email at ucsf.edu

Dr. Suchi Saria

John C. Malone Endowed Chair; Computer Science, Statistics, Medicine, Health Policy, Johns Hopkins

Verified email at cs.jhu.edu - Homepage

Machine Learning Reasoning under Uncertainty Causal Inference Computational Healthcare


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Big data in health care: using analytics to identify and manage high-risk and high-cost patients DW Bates, S Saria, L Ohno-Machado, A Shah, G Escobar Health Affairs 33 (7), 1123-1131, 2014	1259	2014
Do no harm: a roadmap for responsible machine learning for health care (vol 25, pg 1337, 2019) J Wiens, S Saria, M Sendak, M Ghassemi, VX Liu, F Doshi-Velez, ... NATURE MEDICINE 25 (10), 1627-1627, 2019	596*	2019
Do no harm: a roadmap for responsible machine learning for health care J Wiens, S Saria, M Sendak, M Ghassemi, VX Liu, F Doshi-Velez, K Jung, ... Nature Medicine, 1-4, 2019	582	2019
A targeted real-time early warning score (TREWScore) for septic shock KE Henry, DN Hager, PJ Pronovost, S Saria Science Translational Medicine 7 (299), 299ra122-299ra122, 2015	567	2015
Using Smartphones and Machine Learning to Quantify Parkinson Disease Severity: the Mobile Parkinson Disease Score A Zhan, S Mohan, C Tarolli*, RB Schneider, JL Adams, S Sharma, ... JAMA Neurology, 2018	341	2018
The Clinician and Dataset Shift in Artificial Intelligence SG Finlayson, A Subbaswamy, K Singh, J Bowers, A Kupke, J Zittrain, ... New England Journal of Medicine 385 (3), 283-286, 2021	301	2021
Artificial intelligence in health care: The hope, the hype, the promise, the peril M Matheny, ST Israni, M Ahmed, D Whicher Washington, DC: National Academy of Medicine 10, 2019	272	2019
Minimum information about clinical artificial intelligence modeling: the MI-CLAIM checklist B Norgeot, G Quer, BK Beaulieu-Jones, A Torkamani, R Dias, ... Nature Medicine 26 (9), 1320-1324, 2020	259	2020
Integration of early physiological responses predicts later illness severity in preterm infants S Saria, AK Rajani, J Gould, D Koller, AA Penn Science translational medicine 2 (48), 48ra65-48ra65, 2010	249*	2010
Microsoft Cambridge at TREC 13: Web and Hard Tracks. H Zaragoza, N Craswell, MJ Taylor, S Saria, SE Robertson TREC 4, 1-1, 2004	243	2004
Reliable Decision Support Using Counterfactual Models P Schulam, S Saria Neural Information Processing Systems (NIPS), 2017	202	2017
From development to deployment: dataset shift, causality, and shift-stable models in health AI A Subbaswamy, S Saria Biostatistics 21 (2), 345-352, 2020	179	2020
Reporting guideline for the early stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI B Vasey, M Nagendran, B Campbell, DA Clifton, GS Collins, S Denaxas, ... bmj 377, 2022	164	2022
Preventing Failures Due to Dataset Shift: Learning Predictive Models That Transport A Subbaswamy, P Schulam, S Saria Artificial Intelligence and Statistics (AISTATS), 2018	162	2018
Subtyping: What it is and its role in precision medicine S Saria, A Goldenberg IEEE Intelligent Systems 30 (4), 70-75, 2015	129	2015
Developing Predictive Models Using Electronic Medical Records: Challenges and Pitfalls C Paxton, A Niculescu-Mizil, S Saria AMIA Annual Symposium Proceedings 2013, 1109, 2013	125	2013
Clustering Longitudinal Clinical Marker Trajectories from Electronic Health Data: Applications to Phenotyping and Endotype Discovery P Schulam, F Wigley, S Saria American Association for Artificial Intelligence 29 (3), 2956-2964, 2015	122	2015
A Framework for Individualizing Predictions of Disease Trajectories by Exploiting Multiresolution Structure P Schulam, S Saria Neural Information Processing Systems 28, 2015	117	2015
Learning individual and population level traits from clinical temporal data S Saria, D Koller, A Penn Proceedings of Neural Information Processing Systems, 1-9, 2010	100*	2010
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning P Schulam, S Saria Artificial Intelligence and Statistics (AISTATS), 2019	94	2019

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