Accepted for/Published in: JMIR AI
Date Submitted: Jul 9, 2025
Open Peer Review Period: Aug 5, 2025 - Sep 30, 2025
Date Accepted: Jan 5, 2026
(closed for review but you can still tweet)
Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.
Important Ethical, Technical, and Epidemiological Considerations in an AI tool Production (ETEPAI): a Scoping Review
ABSTRACT
Background:
Artificial intelligence (AI) tools are being developed in a rapid evolving technology. The convergence of ethical, technical, and research methods considerations is crucial for multidisciplinary teams aiming to produce effective AI tools. The success of these tools post-deployment hinges on the intricate interplay between the AI system’s development on its output through rigorous decision-making processes, and stakeholders' capacity to act on the AI's recommendations.
Objective:
This paper synthesizes ethical, technical, and epidemiological considerations (ETEPAI) for all involved in AI tool production, based on established guidelines, checklists, and frameworks.
Methods:
Relevant guidelines, checklists, frameworks, and expert recommendations were systematically identified and synthesized into ETEPAI, an ethical, technical, and epidemiological framework for AI tool development in healthcare. ETEPAI integrates critical considerations across four stages (design, develop, deploy, post-deployment) and three domains (ethics, technical, epidemiological), providing a compact yet comprehensive guide. It includes probing questions, key indicators, and common pitfalls to support high-quality, ethically sound, and clinically relevant AI tools. ETEPAI aligns with EU trustworthiness standards and is supported by a research proposal template and supplementary references to aid implementation and adoption.
Results:
We present probing questions and critical pointers across four stages from the design, development, deployment, and post-deployment highlighting their relevance in healthcare settings. The designing stage aligns with epidemiologic research methodologies, while the development stage emphasizes transparent project execution. Deployment and post-deployment stages focus on real-world implementation. Also included are common pitfalls and challenges to emphasise the importance of due attention to the important of ETEPAI considerations to avoid serious consequences.
Conclusions:
Applying ETEPAI ensures comprehensive, complete, compact and crisp consideration from conception to execution, promoting high-quality, ethically sound, and clinically relevant AI tools. The brevity and conciseness of ETEPAI might be adequate for trained personnel and serve as clear signposts to unprepared stakeholders. Clinical Trial: NA
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Copyright
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