Privacy and confidentiality concerns due to large scale data usage through AI applications

Accuracy and Reliability : AI errors can compromise patient safety 

Data Quality and Bias : Poor or biased datasets lead to inequitable outcomes

“Black-box” models make it hard for clinicians to trust or validate AI decisions

Regulatory and Governance Issues : Absence of clear standards for safety, liability, and ethical use

Stakeholder involvement : Skepticism about AI reliability reduces adoption

Local norms and values: Tools often fail to fit clinical workflows or local contexts

Other (please specify)