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Related Questions
- What are some common pitfalls in medical diagnosis that LLMs might encounter when relying solely on text-based input?
- How can the use of specific medical terminology and jargon impact the accuracy of LLM-generated diagnoses?
- What role can the development of standardized medical prompt templates play in reducing ambiguity in LLM-generated diagnoses?
- Can the incorporation of multimodal input, such as images and medical histories, improve the accuracy of LLM-generated diagnoses?
- What strategies can be employed to mitigate the impact of bias in training data on LLM-generated medical diagnoses?
- How can the use of active learning techniques, such as human-in-the-loop feedback, enhance the accuracy and reliability of LLM-generated diagnoses?
- What are some potential applications of prompt engineering in medical chatbots or virtual assistants to improve patient outcomes?
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