Clinical decision-making system and method for cervical lesions

Abstract

The invention discloses a clinical decision-making system and method for cervical lesions. The clinical decision-making system comprises: a terminal acquisition module for acquiring case data of a patient; an input conversion module for extracting the case data of the patient and converting into characteristic variables; a data processing module for respectively performing discretization, sparse coding and binarization processing on the characteristic variables; a prediction module for outputting prediction results after the processed characteristic variables are subjected to weight and offsetdimension assignment processing, rectification function relu transformation and softmax regression operation; a conformation and diagnosis module for confirming final clinical diagnosis results and providing true labels for the prediction results; a data center module for receiving and storing all case data of the patient and periodically iterating the prediction module based on all data; and a display module for displaying the prediction results, the diagnosis results and health guidance advice. The clinical decision-making system and method provided by the invention can improve specificityand accuracy of a current cervical cancer screening strategy, and realize big data sharing and integrated network management of cervical cancer screening.

Description

technical field [0001] The invention relates to the field of medical and health technology, in particular to the field of data mining and deep learning, and in particular to a clinical decision-making system for cervical lesions and a method thereof. Background technique [0002] Data mining is an interdisciplinary branch of computer science. It is the computational process of discovering patterns in relatively large data sets using approaches at the intersection of artificial intelligence, machine learning, statistics, and databases. The overall goal of the data mining process is to extract information from a data set and transform it into an understandable structure for further use. Often used in large-scale data or information processing (data acquisition, data extraction, data storage, data analysis, and data statistics), as well as applications in decision support systems (including artificial intelligence, machine learning, and business intelligence). [0003] The ac...

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Problems solved by technology

The disadvantages are as follows: 1. There are disputes in the primary screening examination scheme, that is, TCT and HPV single screening or the combination of the two, and the reported diagnostic value indicators of different schemes are different among studies; 2. The HPV kit certified by the United States is not available in my country. It has been promoted, and the lack of authoritatively certified HPV detection kits in China has led to diverse and disorderly screening methods in China, which has laid hidden dangers for medical disputes; 3. The specificity is low. Among the patients receiving cervical cancer screening in my country, more than 50% High-risk patients have no high-grade cervical lesions or cancers confirmed by pathological examination, resulting in serious waste of medical resources, over-referral of colposcopy, and over-medication of patients; 4. Increase the incidence of complications and bring unnecessary pain to patients; 5. Single screening factor included

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