Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment

Jia Li; Zi-Chun Zhou; Zhen-Chang Wang; Han Lv

doi:10.1186/s40779-026-00684-w

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Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment

PERSPECTIVE | Updated：2026-08-20

- Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment
- Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment
- Military Medical Research 2026年13卷第6期页码：861-868
- Affiliations：
  
  Department of Radiology, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
  Department of Health Data Science, School of Medical Technology, Capital Medical University, Beijing 100050, China
  Precision and Intelligence Medical Imaging Lab, Beijing Friendship Hospital, Capital Medical University, Beijing 100050, China
- Author bio：
  
  * Zhen-Chang Wang cjr.wzhch@vip.163.com
  Han Lv chrislvhan@126.com
- Funds：
  
  the National Natural Science Foundation of China(62522119);the Beijing Natural Science Foundation(7242267;L242024;7254539);the Capital Medical University(B2408);the Seed Program of Beijing Friendship Hospital, Capital Medical University(YYZZ202334)
- DOI：10.1186/s40779-026-00684-w
  中图分类号：
- 收稿：2025-08-17，
  
  录用：2026-01-28，
  
  网络首发：2026-02-10，
  
  纸质出版：2026-06
- Accepted：
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Jia Li, Zi-Chun Zhou, Zhen-Chang Wang, 等. Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment[J]. Military Medical Research, 2026,13(6):861-868.

Jia Li, Zi-Chun Zhou, Zhen-Chang Wang, et al. Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment[J]. Military Medical Research, 2026, 13(6): 861-868.
Jia Li, Zi-Chun Zhou, Zhen-Chang Wang, 等. Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment[J]. Military Medical Research, 2026,13(6):861-868. DOI： 10.1186/s40779-026-00684-w.

Jia Li, Zi-Chun Zhou, Zhen-Chang Wang, et al. Prioritizing human-AI collaboration in healthcare: the TRIAD framework for trustworthy governance, real-world, and integrated adaptive deployment[J]. Military Medical Research, 2026, 13(6): 861-868. DOI： 10.1186/s40779-026-00684-w.

摘要

Abstract

Artificial intelligence (AI) and big data are reshaping the healthcare landscape. However

clinical value depends on how well systems augment clinicians and fit into routine workflows. To this end

we introduce the TRIAD frame-work: trustworthy governance

real-world clinical value

and integrated adaptive deployment

to guide the develop-ment

validation

and deployment of clinical AI. TRIAD requires explicit data provenance and intended use

fairness auditing

and calibrated uncertainty. This framework evaluates the human-AI team in real workflows using teamlevel metrics

including accuracy

safety

workload

and patterns of acceptance

editing

and overriding. Deployment proceeds via staged rollouts with preregistered guardrails and continuous monitoring of performance and subgroup impact. TRIAD views intelligence as a property of the human-AI team rather than the AI model alone. Aligning gov-ernance

evaluation

and deployment around clinicians and patients enables durable gains in safety

equity

efficiency

and experience

thereby elevating clinical value.

关键词

Keywords

references

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