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.
Highlights
Various kinds of malignant lesions may develop in different areas of the body, among the illnesses that pose a danger to people’s lives
Radical surgery for cervical cancer coupled with radiation and chemotherapy is the sole option if the tumor has progressed to an advanced stage and most lymph nodes have been metastasized or invaded [2]
The use of a type of data mining algorithm for the intelligent diagnosis of cervical cancer has important practical significance, especially the valuable information contained in a large amount of medical data cancer diagnosis promotes
Summary
Various kinds of malignant lesions may develop in different areas of the body, among the illnesses that pose a danger to people’s lives. The application fields of related data mining algorithms for processing big data are very wide, including different fields such as medical treatment, medicine, business activities, science, and social practice networks. This has a lot to do with what we do on a daily basis. The use of a type of data mining algorithm for the intelligent diagnosis of cervical cancer has important practical significance, especially the valuable information contained in a large amount of medical data cancer diagnosis promotes
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