Articles with public access mandates - Peter SchulamLearn more
Available somewhere: 8
A review of challenges and opportunities in machine learning for health
M Ghassemi, T Naumann, P Schulam, AL Beam, IY Chen, R Ranganath
AMIA Summits on Translational Science Proceedings 2020, 191, 2020
Mandates: US National Institutes of Health, Natural Sciences and Engineering Research …
Reliable decision support using counterfactual models
P Schulam, S Saria
Advances in neural information processing systems 30, 2017
Mandates: US National Science Foundation, US Department of Defense
Reporting and implementing interventions involving machine learning and artificial intelligence
DW Bates, A Auerbach, P Schulam, A Wright, S Saria
Annals of internal medicine 172 (11_Supplement), S137-S144, 2020
Mandates: US Department of Defense, US National Institutes of Health, Gordon and Betty …
Active learning for decision-making from imbalanced observational data
I Sundin, P Schulam, E Siivola, A Vehtari, S Saria, S Kaski
International conference on machine learning, 6046-6055, 2019
Mandates: Academy of Finland
Disease trajectory maps
P Schulam, R Arora
Advances in neural information processing systems 29, 2016
Mandates: US National Science Foundation
Factors associated with physicians’ prescriptions for rheumatoid arthritis drugs not filled by patients
HJ Kan, K Dyagilev, P Schulam, S Saria, H Kharrazi, D Bodycombe, ...
Arthritis research & therapy 20, 1-12, 2018
Mandates: Patient-Centered Outcomes Research Institute
Development and validation of ARC, a model for anticipating acute respiratory failure in coronavirus disease 2019 patients
S Saria, P Schulam, BJ Yeh, D Burke, SD Mooney, CT Fong, JE Sunshine, ...
Critical care explorations 3 (6), e0441, 2021
Mandates: US National Science Foundation, US National Institutes of Health
Active Learning for Improving Decision-Making from Imbalanced Data
I Sundin, P Schulam, E Siivola, A Vehtari, S Saria, S Kaski
Mandates: Academy of Finland
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