Understanding Responsible Development in AI-Based Clinical Prediction Models for Mortality: Protocol for a Scoping Review

This review will provide a comprehensive summary of AIPMs that predict mortality, highlighting the specific elements included in their development. Informed by the responsible research and innovation (RRI) framework, we will consider interest-holder engagement, interdisciplinary collaboration, and computational and clinical ethics will in the context of the four RRI dimensions: anticipation, reflexivity, inclusion, and responsiveness.

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Publication Details

Journal
JMIR Research Protocols
Published
2026-01-16
DOI
https://doi.org/10.2196/80325
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

Understanding Responsible Development in AI-Based Clinical Prediction Models for Mortality: Protocol for a Scoping Review

Jessalyn K. Holodinsky, Jessica Simon, Zack Marshall, Riley Martens
JMIR Research Protocols
Artificial Intelligence in Healthcare and Education
article

Understanding Responsible Development in AI-Based Clinical Prediction Models for Mortality: Protocol for a Scoping Review

Jessalyn K. Holodinsky, Jessica Simon, Zack Marshall, Riley Martens
article en

Abstract

This review will provide a comprehensive summary of AIPMs that predict mortality, highlighting the specific elements included in their development. Informed by the responsible research and innovation (RRI) framework, we will consider interest-holder engagement, interdisciplinary collaboration, and computational and clinical ethics will in the context of the four RRI dimensions: anticipation, reflexivity, inclusion, and responsiveness.

JMIR Research ProtocolsVol. 15
University of Calgary (CA), McGill University (CA)
Openalex Percentile: Top 87%
Artificial Intelligence in Healthcare and Education
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