The “Papers with Code” repository highlights recent advancements in artificial intelligence (AI) applied to healthcare, specifically addressing question answering in the MedQA dataset. Khosravi et al. (2024) conducted a thematic analysis of AI’s role in healthcare decision-making, exploring its transformative potential. Various studies, including those by Nath (2024) and Nori et al. (2023), examine the integration of large language models (LLMs) within clinical workflows, assessing their efficacy in patient interactions and medical challenges. Experimental benchmarks like MedBench and MedHallu focus on evaluating LLM performance in clinical settings, particularly in terms of accuracy and hallucinations. Researchers like Carl et al. (2025) and Raji et al. (2025) emphasize the importance of meticulous evaluation methodologies. As AI continues to evolve, its applications in healthcare, including question answering and decision-making, are critical for enhancing patient care and operational efficiency in medical environments. For further insights, the original papers can be explored in reputable databases.
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