Abstract
The intelligent diagnosis of cervical cancer by using a class of data mining algorithms has important practical significance. In particular, the useful information included in a significant quantity of medical data may not only discreetly boost the development of medical technology but also detect cervical cancer in the future. This paper improves the data mining algorithm and combines image recognition technology and data mining technology to extract and analyze image features. Moreover, this paper makes full use of the information contained in the image to realize the segmentation of the cervical cancer cell image, select the feature vector according to the characteristics of the cervical cancer cell, and use the statistical classification method to design the classifier. The test results show that the automatic recognition effect of this system is good, and it has a good auxiliary diagnosis effect. Therefore, it can be verified in clinical practice in the follow-up.