Healthcare organizations need to focus on three types of risks when deploying:
- Boundaries of responsibility: Model outputs must be labeled "for reference only" and any clinical decisions must be reviewed by a licensed physician to avoid direct substitution of professional judgment.
- Privacy: Real medical records should be desensitized when processing, API calls need to be encrypted transmission, it is recommended to be deployed in the local environment
- Knowledge update: Medical knowledge is highly current and models need to be regularly updated with the latest guidelines, drug databases (official recommendation is at least quarterly)
A declaration of model source is also required for commercial use as per Apache 2.0 license requirements. It is recommended that a manual review process be established to perform a 100% review of outputs in high-risk areas (e.g., cancer diagnosis).
This answer comes from the articleBaichuan-M2: A Large Language Model for Augmented Reasoning in HealthcareThe
May not be reproduced without permission:AI productivity tools " What are the ethical risks of using Baichuan-M2-32B in healthcare organizations?
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