A method for scoring the cure probability of potential treatment options based on patient detection information

Abstract

The invention belongs to the field of deep learning analysis, and discloses a method for scoring the cure probability of a potential treatment plan based on patient detection information. The method includes the following steps: (S1) collecting training data; (S2) establishing a logistic regression model and training; (S3) respectively establishing the unet model and the three-dimensional convolutional neural network model and training; (S4) complementing the training data, and obtaining the survival score of any patient corresponding to the training data in each day of the treatment process; (S5) Establish a long short-term memory network LSTM model and train it; (S6) Randomize a potential treatment plan, and predict the survival score on the N+2 day, so that the potential treatment plan can be scored. By improving the overall process design of the method and the system, the present invention can specifically quantify the patient's condition from the perspective of big data analysis, and score the cure probability of the potential treatment plan.

Description

technical field [0001] The invention belongs to the field of deep learning analysis, and more particularly, relates to a method for scoring the cure probability of a potential treatment plan based on patient detection information. A system corresponding to the method can also evaluate the cure probability of a potential treatment plan based on the patient detection information. score. Background technique [0002] For a type of disease, the detection values ​​of patients often contain a lot of information. At present, doctors' treatment for patients is based on experience and their own judgments on the patient's condition. Individual differences are large, and misdiagnosis may occur due to various reasons, and the diagnosis plan may also be given ill-considered. [0003] Pulmonary diseases, in addition to being reflected in clinical examination information (such as blood tests and urine tests), can often be judged by CT images of patients' lungs. Combining various data can...

AI Technical Summary

Problems solved by technology

At the same time, there is currently no real-time update prediction method for the treatment plan. This invention hopes to use the patient's examination results and treatment plan to give a treatment plan with a higher probability of cure, and provide reasonable suggestions and references for doctors.

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