Anti-medical institution medical insurance fraud behavior supervision method based on integrated learning and deep learning

The invention relates to the technical field of medical treatment, in particular to a method for supervising anti-medical institution medical insurance fraudulent behaviors based on integrated learning and deep learning, and the method specifically comprises the following steps: S1, data collection and selection; s2, data cleaning and preprocessing; s3, performing data feature engineering; s4, carrying out data modeling fusion; s5, deploying a data model and updating data; according to the anti-medical-insurance-fraud supervised learning method based on integrated learning and deep learning, integrated learning and deep learning are combined to solve the problems that an existing anti-medical-insurance-fraud model is limited in effect on high-dimensional complex data, the recognition accuracy is low and the pain point is low; the method can process a large amount of complex data and changing fraud means, improves the accuracy and efficiency of fraud behavior recognition, adapts to more complex and diversified