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Rich Caruana

Showing results (1-10 of 13) with videos related to

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Nature Communications|November 30, 2023
Augmenting interpretable models with large language models during trainingChandan Singh, Armin Askari, Rich Caruana, et al.
NPJ Digital Medicine|November 21, 2025
The hidden risk of round numbers and sharp thresholds in clinical practiceBenjamin J Lengerich, Rich Caruana, Mark E Nunnally, et al.
Medrxiv : the Preprint Server for Health Sciences|December 21, 2021
Time-Varying Mortality Risk Suggests Increased Impact of Thrombosis in Hospitalized Covid-19 PatientsBenjamin J Lengerich, Mark E Nunnally, Yin Aphinyanaphongs, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|January 20, 2004
Evaluating the C-section rate of different physician practices: using machine learning to model standard practiceRich Caruana, Radu S Niculescu, R Bharat Rao, et al.
Proceedings. AMIA Symposium|December 5, 2002
Machine learning for sub-population assessment: evaluating the C-section rate of different physician practicesRich Caruana, Radu S Niculescu, R Bharat Rao, et al.
Journal of Biomedical Informatics|May 3, 2022
Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case studyBenjamin J Lengerich, Mark E Nunnally, Yin Aphinyanaphongs, et al.
American Journal of Obstetrics & Gynecology MFM|June 8, 2024
Interpretable machine learning predicts postpartum hemorrhage with severe maternal morbidity in a lower-risk laboring obstetric populationBenjamin J Lengerich, Rich Caruana, Ian Painter, et al.
Journal of Healthcare Informatics Research|January 26, 2024
Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal OutcomesTomas M Bosschieter, Zifei Xu, Hui Lan, et al.
Arthroplasty (London, England)|February 27, 2026
Exploring the optimal age for total knee arthroplasty to minimize risk of adverse outcomes: machine learning analysis of a statewide cohortChloe Heiting, Yiyuan Wu, Susan M Goodman, et al.
The Journal of the American Academy of Orthopaedic Surgeons|June 3, 2026
A Machine Learning Approach to Determine the Optimal Age for Total Hip Arthroplasty: When Is Risk for Adverse Outcomes Lowest?Chloe Heiting, Yiyuan Wu, Susan M Goodman, et al.
Pageof 2

Showing results (1-10 of 13) with videos related to

Sort By:
Pageof 2
Nature Communications|November 30, 2023
Augmenting interpretable models with large language models during trainingChandan Singh, Armin Askari, Rich Caruana, et al.
NPJ Digital Medicine|November 21, 2025
The hidden risk of round numbers and sharp thresholds in clinical practiceBenjamin J Lengerich, Rich Caruana, Mark E Nunnally, et al.
Medrxiv : the Preprint Server for Health Sciences|December 21, 2021
Time-Varying Mortality Risk Suggests Increased Impact of Thrombosis in Hospitalized Covid-19 PatientsBenjamin J Lengerich, Mark E Nunnally, Yin Aphinyanaphongs, et al.
AMIA ... Annual Symposium Proceedings. AMIA Symposium|January 20, 2004
Evaluating the C-section rate of different physician practices: using machine learning to model standard practiceRich Caruana, Radu S Niculescu, R Bharat Rao, et al.
Proceedings. AMIA Symposium|December 5, 2002
Machine learning for sub-population assessment: evaluating the C-section rate of different physician practicesRich Caruana, Radu S Niculescu, R Bharat Rao, et al.
Journal of Biomedical Informatics|May 3, 2022
Automated interpretable discovery of heterogeneous treatment effectiveness: A COVID-19 case studyBenjamin J Lengerich, Mark E Nunnally, Yin Aphinyanaphongs, et al.
American Journal of Obstetrics & Gynecology MFM|June 8, 2024
Interpretable machine learning predicts postpartum hemorrhage with severe maternal morbidity in a lower-risk laboring obstetric populationBenjamin J Lengerich, Rich Caruana, Ian Painter, et al.
Journal of Healthcare Informatics Research|January 26, 2024
Interpretable Predictive Models to Understand Risk Factors for Maternal and Fetal OutcomesTomas M Bosschieter, Zifei Xu, Hui Lan, et al.
Arthroplasty (London, England)|February 27, 2026
Exploring the optimal age for total knee arthroplasty to minimize risk of adverse outcomes: machine learning analysis of a statewide cohortChloe Heiting, Yiyuan Wu, Susan M Goodman, et al.
The Journal of the American Academy of Orthopaedic Surgeons|June 3, 2026
A Machine Learning Approach to Determine the Optimal Age for Total Hip Arthroplasty: When Is Risk for Adverse Outcomes Lowest?Chloe Heiting, Yiyuan Wu, Susan M Goodman, et al.
Pageof 2