Method of recommending personalized treatment scheme for stroke patient

Abstract

The invention discloses a method of recommending a personalized treatment scheme for a stroke patient. The method comprises the following steps: S1, preprocessing text information about physical examination and evaluation results in electronic medical records of patients; S2, expressing words, sentences and documents in the physical examination and evaluation results in the electronic medical records of the patients in a vector manner; S3, training a neural network model based on document vectors to obtain a personalized treatment scheme recommendation model; and S4, carrying out unified dataexpression, word segmentation and text filtering processing on the physical examination and evaluation results in an electronic medical record of a new patient, then carrying out document vector representation, and inputting represented document vectors into the personalized treatment scheme recommendation model to obtain a recommended personalized treatment scheme. According to the method, evaluation and physical examination information in the electronic medical record of the patient is taken as a document, the process of personalized treatment scheme recommendation is converted into a multi-label classification problem, the personalized treatment scheme can be recommended according to the physical examination results and the evaluation results of the patient, an auxiliary decision is provided for a doctor, and the burden of the doctor is reduced.

Description

technical field [0001] The invention relates to a method for recommending a personalized treatment scheme for stroke patients. Background technique [0002] Stroke is a disease whose main clinical manifestations are cerebral ischemia and hemorrhagic injury, also known as cerebral apoplexy or cerebrovascular accident. Stroke has the characteristics of high morbidity, high mortality and high disability rate, which brings a great burden to patients' families and society. Clinical observations show that reasonable rehabilitation treatment and rehabilitation training are effective ways to improve the physical function of stroke patients and reduce mortality. Due to the large differences in the condition and individuality of patients, rehabilitation treatment needs to be targeted, and it is particularly important to tailor a personalized rehabilitation treatment plan for patients. At present, doctors usually formulate rehabilitation treatment plans based on the assessment result...

AI Technical Summary

Problems solved by technology

[0006] Clinically, physicians formulate treatment plans for patients based on patient status and evaluation results, and there are the following problems: 1) The scores of patient evaluation results are the same, but there are differences between different patients, and the treatment plan needs to be formulated in consideration of the patient's own physical state

2) Due to the subjective influence of doctors, there are differences in the treatment plans of different doctors

[0007] The treatment plan recommendation method based on data mining, machine learning and other technologies is mainly based on the similarity of patient symptoms, and most of them can only recommend dosage or medication type; and there are cases in clinical practice where patients have similar symptoms but different diseases. Recommendations by symptoms may result in unusable recommendations

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