This paper is in the following e-collection/theme issue:

E-Health Policy and Health Systems Innovation (208) Research Instruments, Questionnaires, and Tools (545) Theoretical Frameworks and Concepts (232) eHealth Infrastructures (310) Artificial Intelligence (1214) Artificial Intelligence (122)

Published on in Vol 25 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/48496, first published .
A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study

A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study

A Comprehensive, Valid, and Reliable Tool to Assess the Degree of Responsibility of Digital Health Solutions That Operate With or Without Artificial Intelligence: 3-Phase Mixed Methods Study

Authors of this article:

Pascale Lehoux1 Author Orcid Image ;   Robson Rocha de Oliveira2 Author Orcid Image ;   Lysanne Rivard2 Author Orcid Image ;   Hudson Pacifico Silva2 Author Orcid Image ;   Hassane Alami3 Author Orcid Image ;   Carl Maria Mörch4 Author Orcid Image ;   Kathy Malas5 Author Orcid Image
Article Authors Cited by (2) Tweetations (11) Metrics
All Time | Last Month | Last Six Months | Last Year
There are currently no tweets available for this article within the specified range.