Lung cancer frontier trend prediction method based on multi-label classification

Abstract

The invention discloses a lung cancer frontier trend prediction method based on multi-label classification, and the method comprises the steps: collecting serial numbers, titles, abstracts and publishing dates of papers in the field of lung cancer research, and forming a data set; formulating a category set corresponding to themes of papers in the lung cancer research field; labeling the collectedabstract text according to the category set; preprocessing the text in the data set; dividing the data set into a training set and a verification set according to the publishing date of the paper; inputting the training sample into a Bert-based multi-label classification network, setting a loss function loss, performing back propagation on a loss value, updating a weight parameter, and continuously iterating the training network until the loss value does not drop any more; and classifying the data of the verification set by using the trained classification network to obtain a classification result. According to the method, the problem that the traditional multi-label algorithm neglects the label correlation is improved; meanwhile, the artificial intelligence technology is combined with medical treatment, and a new thought for trend prediction in the medical field is provided.

Description

technical field [0001] The invention belongs to the field of deep learning and natural language processing, and specifically relates to a method for predicting frontier trends of lung cancer based on multi-label classification. Background technique [0002] Medical problems have always been one of the most concerned issues of the people, and cancer, as a malignant tumor, has always been a serious threat to human life and health due to its high mortality and high morbidity. In 2019, the International Agency for Research on Cancer assessed the mortality and incidence rates of 36 cancers in 185 countries around the world. Among them, the incidence of lung cancer ranks first. The incidence of lung cancer in China is higher than that in the world. [0003] In order to protect people's life and health, medical workers have conducted a lot of research on the pathogenesis, treatment, gene correlation and other aspects of lung cancer, and achieved a lot of results. Tracking the de...

AI Technical Summary

Problems solved by technology

In the face of scientific research tasks, it takes a lot of energy to track the latest research hotspots before carrying out research work

On the other hand, the number of papers that can be inspected by humans is limited, and it is impossible to fully grasp them in the face of tens of thousands of documents.

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