Duke University
Relevante Arbeiten
Meistzitierte Publikationen im Bereich Gesundheit & MedTech
Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead
Cynthia Rudin
2019 · 8.666 Zit.
Effect of Clinical Decision-Support Systems
Tiffani J Bright, Anthony Wong, Dhurjati Ravi et al.
2012 · 1.231 Zit.
Do no harm: a roadmap for responsible machine learning for health care
Jenna Wiens, Suchi Saria, Mark Sendak et al.
2019 · 964 Zit.
Comparing Amazon’s Mechanical Turk Platform to Conventional Data Collection Methods in the Health and Medical Research Literature
Karoline Mortensen, Taylor L. Hughes
2018 · 456 Zit.
Evaluation of Combined Artificial Intelligence and Radiologist Assessment to Interpret Screening Mammograms
Thomas Schaffter, Diana S.M. Buist, Christoph I. Lee et al.
2020 · 410 Zit.
Using Digital Health Technology to Better Generate Evidence and Deliver Evidence-Based Care
Abhinav Sharma, Robert A. Harrington, Mark McClellan et al.
2018 · 341 Zit.
The emerging science of quantitative imaging biomarkers terminology and definitions for scientific studies and regulatory submissions
Larry G. Kessler, Huiman X. Barnhart, Andrew J. Buckler et al.
2014 · 285 Zit.
The role of machine learning in clinical research: transforming the future of evidence generation
E. Hope Weissler, Tristan Naumann, Tomas Andersson et al.
2021 · 277 Zit.
Recommendations for Reporting Machine Learning Analyses in Clinical Research
Laura Stevens, Bobak J. Mortazavi, Rahul C. Deo et al.
2020 · 260 Zit.
Human–machine partnership with artificial intelligence for chest radiograph diagnosis
Bhavik N. Patel, Louis Rosenberg, Gregg Willcox et al.
2019 · 251 Zit.
Presenting machine learning model information to clinical end users with model facts labels
Mark Sendak, Michael Gao, Nathan Brajer et al.
2020 · 223 Zit.
Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study
Mark Sendak, William Ratliff, Dina Sarro et al.
2019 · 223 Zit.
Development and validation of machine learning models to identify high-risk surgical patients using automatically curated electronic health record data (Pythia): A retrospective, single-site study
Kristin Corey, Sehj Kashyap, Elizabeth Lorenzi et al.
2018 · 209 Zit.
"The human body is a black box"
Mark Sendak, Madeleine Clare Elish, Michael Gao et al.
2020 · 180 Zit.
Digital Medicine: A Primer on Measurement
Andrea Coravos, Jennifer C. Goldsack, Daniel R. Karlin et al.
2019 · 162 Zit.