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Related Questions
- What are the primary challenges in fine-tuning medical language models for specific domains?
- How does domain-specific fine-tuning affect the performance of medical language models in terms of accuracy and robustness?
- Can you elaborate on the differences between domain adaptation and domain-specific fine-tuning in the context of medical language models?
- What techniques are used to improve the explainability and interpretability of medical language models, and how do they relate to domain-specific fine-tuning?
- How does the choice of pre-training data and fine-tuning objectives impact the explainability and interpretability of medical language models?
- What role does transfer learning play in the fine-tuning of medical language models, and how does it affect explainability and interpretability?
- Can you discuss the potential risks and limitations of relying on domain-specific fine-tuning for medical language models, particularly in terms of generalizability and robustness?
- How do domain-specific fine-tuning and explainability techniques impact the deployment and trustworthiness of medical language models in real-world clinical settings?
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