Decision classification method for fusion reasoning and learning of liquid-based cytological examination

Abstract

The invention discloses a decision classification method for fusion reasoning and learning of liquid-based cytological examination, which comprises the following steps: 1) data and ontology preparation: constructing a data set for a decision target and an ontology related to the data, extracting a plurality of associated data features between the data set and the ontology, and taking the associated data features as sub-features of target features; 2) neural network and rule construction: training a neural network set comprising a target feature clustering device and a plurality of sub-featureclassifiers, and constructing an inference rule related to a decision target; and 3) knowledge reasoning and neural network fusion: fusing knowledge reasoning and machine learning to realize knowledgerule reasoning supporting a machine learning result, combining a reasoning result with an evolution method of the machine learning result, and analyzing a processing result. According to the method,two ways of knowledge reasoning and machine learning are fused, the classification accuracy is improved, meanwhile, the result has interpretability through an evolution method, and the reliability ofthe result is gradually improved.

Description

technical field [0001] The invention belongs to the field of computer software development, and in particular relates to a decision classification method integrating reasoning and learning. Background technique [0002] Cervical cancer is one of the serious health problems, which affects nearly 500,000 women every year in the world. The use of Pap smears to screen cervical cancer has created a precedent for cervical cancer screening. With the gradual application of computer technology in the medical field, the screening method of TCT combined with descriptive diagnosis (TBS) has become a widely used high-accuracy screening method today. cervical cancer screening techniques. [0003] Liquid-based cytology (TCT) technology can effectively reduce the rate of missed diagnosis of cervical lesions, but the labor cost of TCT examination is relatively high. The cervical cell sample required for screening contains tens of thousands of cervical cells, and the process of observing an...

AI Technical Summary

Problems solved by technology

[0006] Although both knowledge reasoning and machine learning have been greatly developed, many complex problems in reality cannot be solved by only one of them

Perception and reasoning are the basic abilities of human beings. However, in the current machine learning system, the perception and reasoning modules are difficult to be compatible.

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