Non-small cell lung cancer risk prediction method based on machine learning

Abstract

The invention provides a non-small cell lung cancer risk prediction method based on machine learning, and the method comprises the steps of carrying out the typical feature extraction of a chest CT image of a patient, and recording the typical feature as a CT image feature; obtaining CT image features of all patients in the sampling sample, forming a sample data set by combining clinical pathologyfeatures of all patients in the sampling sample, and preprocessing the CT image features in the sample data set; dividing the preprocessed sample data set into a test set and a training set; and performing feature screening on CT image features and clinical pathology features of patients in the divided test set and training set, and based on the training set subjected to feature screening, performing prediction training on high and low risks of non-small cell lung cancer by adopting a joint Nomogram model to obtain a non-small cell lung cancer risk prediction result. The invention can accumulate the experience of excellent doctors and experts, so as to copy the experience to other small cities and hospitals for popularization and application, improve the risk prediction accuracy, and improve the treatment effect of patients.

Description

Technical field [0001] The present invention belongs to the field of medical technology, and more particularly to a risk prediction method of non-small cell lung cancer based on machine learning. Background technique [0002] Lung cancer is one of the most common malignant tumors in the world, and has become the first place in the cause of malignant tumors in urban population in my country. About 75% of patients with non-small cell lung cancer were already in the middle and late stage, and the 5-year survival rate was very low. If the patient does not get timely diagnosis and treatment, it will miss the best treatment opportunity to face life. By combining CT image characteristics and clinical pathological characteristics, non-small cell lung cancer risk prediction, prediction results are divided into high risks and low risks, and doctors can arrange reasonable treatment programs according to the forecast results, and improve the treatment effect. However, according to CT imaging...

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a method for predicting the risk of non-small cell lung cancer based on machine learning, which solves the problem that the risk of non-small cell lung cancer is predicted based on the ability and experience of doctors at present, and the prediction results show large differences and the prediction is inaccurate.

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