Abstract
This paper investigates the development and evaluation of intelligent medical decision support systems. Firstly, the current status of such systems is introduced, including technological advancements, clinical applications, and challenges faced. Subsequently, the overall framework design, key module design and implementation, system integration, and debugging are elaborated in detail. Finally, using the publicly available MIMIC medical dataset, a comprehensive evaluation and analysis of the system are conducted in a high-performance environment. The results indicate that the optimized system can achieve high accuracy and AUC. However, there is a slight decrease in effectiveness when dealing with rare diseases, and occasional false positives in certain high-risk situations. Overall, the research confirms the promising application prospects of such systems and provides a framework and path for future development.
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