Auxiliary diagnosis method for multifocal motor neuropathy and peacetime mountain disease, computing device and storage medium

By combining feature extraction from electromyography, serological and muscle biopsy data with random forest or XGBoost models, the diagnosis of multifocal motor neuropathy and Pingshan disease has been automated and standardized. This solves the problem of misdiagnosis and missed diagnosis caused by reliance on doctors' subjective judgment in existing technologies, and improves the accuracy and efficiency of diagnosis.

CN121366709APending Publication Date: 2026-01-20CENT HOSPITAL AFFILIATED TO SHENYANG MEDICAL COLLEGE
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Patent Information

Application Number
CN202511280143.7
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-09-09
Publication Date
2026-01-20

AI Technical Summary

Technical Problem

In the current technology, the diagnosis of multifocal motor neuropathy (MMN) and Hirayama disease relies on the subjective judgment of doctors, lacking unified standards and objective indicators, resulting in a high rate of misdiagnosis and missed diagnosis, and making it difficult to make a clear judgment in the early stages.

Method used

By performing electromyography, serological examination, and muscle biopsy on the subjects, feature vectors are extracted and input into a pre-trained classification model based on the decision tree algorithm. The model is then combined with a random forest or XGBoost model for diagnosis, outputting the classification probability and comparing it with a preset threshold to automatically generate diagnostic results and provide feature importance information.

Benefits of technology

It enables automated and standardized diagnosis of multifocal motor neuropathy and Pingshan disease, reducing the rate of misdiagnosis and missed diagnosis, improving diagnostic efficiency, enhancing the interpretability and credibility of diagnostic results, reducing reliance on highly experienced physicians, and is applicable to primary hospitals, thus reducing resource consumption.

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Abstract

The invention relates to the technical field of medical auxiliary diagnosis, and particularly discloses an auxiliary diagnosis method for multifocal motor neuropathy and peingshan disease, which comprises the following steps: step S100: performing electromyogram detection, serological examination and muscle biopsy on an examined object to obtain electromyogram signal data, serological examination result data and muscle biopsy result data; s200, performing feature extraction on the electromyogram signal data, the serological examination result data and the muscle biopsy result data, and combining the extracted features to form a feature vector; step S300, obtaining output classification probabilities, wherein the classification probabilities correspond to the multi-focus motor neuropathy and the Pingshan disease, and excluding three categories of the multi-focus motor neuropathy and the Pingshan disease; electromyogram signals, serological examination and muscle biopsy multi-source data are fused to extract core features, a classification model is constructed by using a random forest or XGBoost algorithm, and the automation and standard unification of the whole diagnosis process are realized.
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Citation Information

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