Risk factor-based cancer auxiliary discrimination method, equipment and program product

Through the cancer-assisted discrimination method based on risk factors, using risk discrimination models and feature importance scoring, the problem of lack of scientific risk assessment in renal cancer treatment decisions was solved, and more accurate renal cancer risk assessment and personalized treatment plan recommendations were achieved.

CN120221048APending Publication Date: 2025-06-27PEKING UNIVERSITY FIRST HOSPITAL (PEKING UNIVERSITY FIRST CLINICAL MEDICAL COLLEGE)
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Patent Information

Application Number
CN202510351609.1
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2025-03-24
Publication Date
2025-06-27

AI Technical Summary

Technical Problem

The lack of scientific and systematic risk assessment tools in the treatment decisions of renal cancer in the existing technology, which makes it difficult to dynamically adjust the treatment strategies, balance the efficacy and toxicity, integrate multidisciplinary opinions, and deal with tumor heterogeneity.

Method used

Provide a cancer-assisted discrimination method based on risk factors. By acquiring clinical data, extracting risk factor characteristics, using a risk discrimination model (through information gain and/or Gini index gain training), and scoring in combination with feature importance, it recommends treatment options.

Benefits of technology

This method can help doctors diagnose renal cancer risk results more objectively and comprehensively, optimize treatment plans, and improve the feasibility and reliability of medical decisions.

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Abstract

The invention relates to the field of intelligent medical treatment, in particular to a cancer auxiliary judgment method and device based on risk factors and a program product. Comprising the steps of obtaining clinical data of a to-be-tested person; performing risk factor feature extraction on the clinical data to obtain risk features; the risk factor characteristics are factors related to cancers and comprise clinical characteristic risk factors, biological characteristic risk factors and treatment related risk factors; and outputting the risk characteristics to a risk discrimination model to obtain a cancer risk result, wherein the risk discrimination model is obtained by calculating information gain and / or Gini index gain training of the risk characteristics. The cancer treatment scheme can be recommended based on clinical information, and the method has good clinical value.
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