Mark Sendak

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

2019 · 893 Zit. · Nature Medicine

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

2020 · 199 Zit. · npj Digital Medicine

Real-World Integration of a Sepsis Deep Learning Technology Into Routine Clinical Care: Implementation Study

2019 · 199 Zit. · JMIR Medical Informatics

"The human body is a black box"

2020 · 166 Zit.

Integrating a Machine Learning System Into Clinical Workflows: Qualitative Study

2020 · 144 Zit. · Journal of Medical Internet Research

A Path for Translation of Machine Learning Products into Healthcare Delivery

2020 · 135 Zit. · EMJ Innovation

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

2019 · 78 Zit. · eGEMs (Generating Evidence & Methods to improve patient outcomes)

Meeting the Moment: Addressing Barriers and Facilitating Clinical Adoption of Artificial Intelligence in Medical Diagnosis

2022 · 74 Zit. · NAM Perspectives

Advancing Artificial Intelligence in Health Settings Outside the Hospital and Clinic

2020 · 59 Zit. · NAM Perspectives

Organizational Governance of Emerging Technologies: AI Adoption in Healthcare

2023 · 40 Zit.

Advancing primary care with Artificial Intelligence and Machine Learning

2021 · 38 Zit. · Healthcare

Development and preliminary testing of Health Equity Across the AI Lifecycle (HEAAL): A framework for healthcare delivery organizations to mitigate the risk of AI solutions worsening health inequities

2024 · 37 Zit. · PLOS Digital Health

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

2019 · 28 Zit. · Nature Medicine

"The Human Body is a Black Box": Supporting Clinical Decision-Making with Deep Learning

2019 · 22 Zit. · arXiv (Cornell University)

Enabling collaborative governance of medical AI

2023 · 21 Zit. · Nature Machine Intelligence