Ten Key Suggestions for LLMs in Medicine |
1. |
Transfer learning, domain adaptation, few-shot learning, and zero-shot learning |
2. |
Reinforcement learning with expert feedback according to an explicit code of ethics |
3. |
Dynamic model with emphasis on more recent and more cited work |
4. |
Robust and specific evaluation metrics and benchmarks, along with clinical validation |
5. |
Data privacy, fairness-aware provisions, and diverse stakeholder involvement |
6. |
Inclusion of patients, caregivers, and other diverse perspectives |
7. |
Education and training prerequisites for the users |
8. |
A regulatory framework for their development, validation, deployment, maintenance, and monitoring |
9. |
Addressing cost and resource implications, exploring efficient models and cloud-based resources |
10. |
Ethical considerations, unbiased models, and mitigation strategies for potential risks and limitations |