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 · 8.047 Zit.
Do no harm: a roadmap for responsible machine learning for health care
Jenna Wiens, Suchi Saria, Mark Sendak et al.
2019 · 893 Zit.
The National COVID Cohort Collaborative (N3C): Rationale, design, infrastructure, and deployment
Melissa Haendel, Christopher G. Chute, Tellen D. Bennett et al.
2020 · 573 Zit.
Using Digital Health Technology to Better Generate Evidence and Deliver Evidence-Based Care
Abhinav Sharma, Robert A. Harrington, Mark McClellan et al.
2018 · 334 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 · 283 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 · 270 Zit.
Recommendations for Reporting Machine Learning Analyses in Clinical Research
Laura Stevens, Bobak J. Mortazavi, Rahul C. Deo et al.
2020 · 250 Zit.
Human–machine partnership with artificial intelligence for chest radiograph diagnosis
Bhavik N. Patel, Louis Rosenberg, Gregg Willcox et al.
2019 · 245 Zit.
Presenting machine learning model information to clinical end users with model facts labels
Mark Sendak, Michael Gao, Nathan Brajer et al.
2020 · 199 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 · 199 Zit.
"The human body is a black box"
Mark Sendak, Madeleine Clare Elish, Michael Gao et al.
2020 · 166 Zit.
Digital Medicine: A Primer on Measurement
Andrea Coravos, Jennifer C. Goldsack, Daniel R. Karlin et al.
2019 · 159 Zit.
Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study
Sahil Sandhu, Anthony Lin, Nathan Brajer et al.
2020 · 144 Zit.
The State of Artificial Intelligence in Nursing Education: Past, Present, and Future Directions
Jennie C. De Gagné
2023 · 141 Zit.
A Path for Translation of Machine Learning Products into Healthcare Delivery
Mark Sendak, Joshua D’Arcy, Sehj Kashyap et al.
2020 · 135 Zit.