Diagnostic Reasoning Prompt

Diagnostic reasoning prompts are being explored to improve the performance and interpretability of large language and vision-language models (LLMs and VLMs) in medical applications, such as diagnosis and report generation. Current research focuses on developing effective prompting strategies, including those incorporating medical knowledge graphs and leveraging techniques like soft prompt learning and few-shot learning, to enhance model accuracy and reduce hallucinations. These advancements aim to bridge the gap between the capabilities of these powerful models and the stringent requirements of clinical practice, ultimately improving the efficiency and reliability of medical diagnosis and documentation.