Duke Institute for Health Innovation

Do no harm: a roadmap for responsible machine learning for health care

Jenna Wiens, Suchi Saria, Mark Sendak et al.

2019 · 944 Zit.

Reporting guideline for the early-stage clinical evaluation of decision support systems driven by artificial intelligence: DECIDE-AI

Baptiste Vasey, Myura Nagendran, Bruce Campbell et al.

2022 · 462 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 · 221 Zit.

Presenting machine learning model information to clinical end users with model facts labels

Mark Sendak, Michael Gao, Nathan Brajer et al.

2020 · 215 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 · 178 Zit.

Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study

Sahil Sandhu, Anthony Lin, Nathan Brajer et al.

2020 · 151 Zit.

A Path for Translation of Machine Learning Products into Healthcare Delivery

Mark Sendak, Joshua D’Arcy, Sehj Kashyap et al.

2020 · 142 Zit.

ChatGPT: promise and challenges for deployment in low- and middle-income countries

Xiaofei Wang, Hayley M. Sanders, Yuchen Liu et al.

2023 · 131 Zit.

The potential for artificial intelligence to transform healthcare: perspectives from international health leaders

Christina Silcox, Eyal Zimlichmann, Katie Huber et al.

2024 · 104 Zit.

A framework for the oversight and local deployment of safe and high-quality prediction models

Armando Bedoya, Nicoleta Economou-Zavlanos, Benjamin A. Goldstein et al.

2022 · 97 Zit.

Machine Learning in Health Care: A Critical Appraisal of Challenges and Opportunities

Mark Sendak, Michael Gao, Marshall Nichols et al.

2019 · 79 Zit.

Translating ethical and quality principles for the effective, safe and fair development, deployment and use of artificial intelligence technologies in healthcare

Nicoleta Economou-Zavlanos, Sophia Bessias, Michael P. Cary et al.

2023 · 45 Zit.

Evaluating the performance of artificial intelligence-based speech recognition for clinical documentation: a systematic review

Johan Y. Y. Ng, Eugene Wang, Xinyan Zhou et al.

2025 · 45 Zit.

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units

Alexander Fenn, Connor Davis, Daniel M. Buckland et al.

2021 · 43 Zit.