Prediction method and system for mass lymph node metastasis of minimal thyroid cancer

Abstract

The invention discloses a thyroid minimal cancer mass lymph node metastasis prediction method and system, and relates to the field of risk prediction, the system comprises a client module, a data acquisition module, a patient database, an intelligent prediction module, a result visualization module and a message reminding module; the prediction system obtains information of a target patient, establishes an intelligent prediction model, and imports the information of the target patient and past data of the target patient into the intelligent prediction model; evaluating and predicting a large number of lymph node metastasis risks of the target patient through the intelligent prediction model, generating reminding information according to an output result of the intelligent prediction model, and sending the reminding information according to a preset mode; and displaying the target patient information and an output result of the intelligent prediction model according to a preset mode. The lymph node metastasis prediction method realizes high-efficiency prediction of lymph node metastasis, and sends a prompt to the doctor for the found high risk, thereby reducing the repeated work of the doctor and improving the processing timeliness of the high-risk patient.

Description

technical field [0001] The present invention relates to the technical field of risk prediction, and more specifically, to a method and system for predicting massive lymph node metastasis of thyroid microcarcinoma. Background technique [0002] Papillary thyroid microcarcinoma is prone to lymph node metastasis, but not all lymph node metastasis is found to indicate a poor prognosis. Long-term follow-up studies have shown that a large number of lymph node metastasis (more than 5) is related to the prognosis of the disease. For patients with thyroid microcarcinoma, most of them are currently treated with surgery or active monitoring and follow-up under the guidance of doctors. For thyroid microcarcinoma patients treated with surgery, preoperative evaluation of a large number of lymph node metastases can help patients choose surgical methods and avoid secondary surgery; for patients with thyroid microcarcinoma who take active monitoring and follow-up as a treatment method, eval...

AI Technical Summary

Problems solved by technology

[0003] Currently, the existing prediction models are based on variables that can only be obtained after surgery, and cannot be judged before surgery; in addition, most of the existing model prediction applications only consider predicting the prognosis of surgical patients, and do not consider the means of active follow-up monitoring Therefore, the practical application of previous models is limited

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