Governance and Implementation Studies

AI governance and effective implementation are critical in medical research because they ensure that AI advances scientific progress while protecting patients, clinicians, and public trust. Without clear governance and thoughtful deployment, even highly accurate AI systems can cause harm or fail to translate into real clinical benefit.

AI governance and implementation are essential to medical research because:

1. Protecting patient safety and wellbeing
AI governance establishes safeguards—such as validation standards, monitoring, and human oversight—to prevent unsafe or inappropriate use of AI-generated insights.

2. Ensuring ethical and responsible use
Governance frameworks address key ethical issues including patient consent, data privacy, bias, and accountability. This is essential in medical research, where misuse of data or biased models can disproportionately harm vulnerable populations.

3. Promoting trust and adoption
Clinicians, patients, and regulators are more likely to accept AI tools when they are transparently governed. Clear rules on how AI systems are developed, evaluated, and used help build confidence that AI supports—not replaces—clinical judgment.

4. Improving research quality and reliability
AI governance enforces standards for data quality, model validation, documentation, and reporting. This improves research reproducibility, reduces false findings, and ensures that research outcomes are scientifically robust and clinically meaningful.

6. Enabling safe and effective implementation
Strong governance ensures AI systems perform as intended in real-world settings and adapt safely over time.


1. HOW READY ARE WE TO TRUST USING AI IN MEDICINE? A study on compliance to governance, engagement of stakeholders and integration into medical system. PI: Prof. Joseph Sung

1. Cher Heng Tan^, Wilson Wen Bin Goh, Jimmy Bok Yan So, Joseph J Y Sung.. Clinical use cases in artificial intelligence: current trends and future opportunities. . Singapore Medical Journal, 65(3): pp. 183-185. DOI: 10.4103/singaporemedj.SMJ-2023-193. Mar 2024. 

2. Thomas Y. Lam, Yueyang Yi ,Fat Kei Cheung, Wilson Wen Bin Goh,  Joseph JY Sung. Su1974 LEVEL OF ACCEPTANCE AND TRUST OF ARTIFICIAL INTELLIGENCE AMONG GASTROENTEROLOGY NURSES. Gastroenterology, 166(5): pp. S-888. DOI: 10.1016/S0016-5085(24)02523-X. May 2024. ##

3. Wilson Wb Goh, Kendrick Ya Chia, Max Fk Cheung, Kalya M Kee, May O Lwin, Peter J Schulz, Minhu Chen, Kaichun Wu, Simon Sm Ng, Rashid Lui, Tiing Leong Ang, Khay Guan Yeoh, Han-Mo Chiu, Deng-Chyang Wu, Joseph Jy Sung. Risk Perception, Acceptance, and Trust of Using AI in Gastroenterology Practice in the Asia-Pacific Region: Web-Based Survey Study. JMIR AI, 3(): pp. e50525. DOI: 10.2196/50525. Mar 2024.