Abstract: In order to solve the problem of the lack of intelligent application in hospital, this paper puts forward a kind of intelligent application related to hospital aided diagnosis and treatment. This algorithm combines an improved genetic algorithm and network center mathematical model to optimize the initial center. Firstly, an improved genetic algorithm is used to obtain the approximate optimal clustering number k of document set, and then the network center and center of gravity mathematical model are used to obtain the optimized initial clustering center, which effectively solves the sensitivity of the algorithm to the initial clustering center, and achieves good experiments result. In the practical application stage, different application rule models are designed and formulated in combination with different medical business scenarios, and the operation effect of the algorithm is tested through practical applications such as intelligent inspection appointment timeliness analysis, intelligent evaluation of blood transfusion quality, surgical risk prediction analysis and auxiliary diagnosis recommendation, and good application results are achieved.

Key words: smart hospital, clustering algorithm, assistant decision-making