Medical Benchmark

Medical benchmarks are standardized datasets and evaluation protocols used to assess the performance of artificial intelligence models in healthcare applications, primarily focusing on improving diagnostic accuracy and clinical decision-making. Current research emphasizes the development of comprehensive benchmarks encompassing diverse medical modalities (imaging, text, physiological signals), evaluating various model architectures including large language models (LLMs) and vision-language models (LVLMs), and exploring different fine-tuning strategies. These benchmarks are crucial for advancing the field by enabling objective comparisons of AI models, identifying their limitations, and ultimately facilitating the development of more reliable and trustworthy AI tools for clinical use.