A system and device for constructing a prediction index of neoadjuvant efficacy of malignant tumors
By using an improved deep convolutional neural network and multi-region analysis, a predictive index system for neoadjuvant efficacy assessment of malignant tumors was constructed. This system enables accurate identification and combined feature prediction of tumor, necrosis, and lymphatic infiltration areas, solving the problems of subjectivity and insufficient quantitative accuracy in existing assessment methods and providing accurate efficacy prediction support.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NANCHANG UNIV
- Filing Date
- 2026-06-24
- Publication Date
- 2026-07-21
AI Technical Summary
Existing methods for assessing neoadjuvant efficacy rely on manual interpretation, which suffers from significant observer variability, insufficient quantitative precision, and neglect of the prognostic value of multi-regional combinations, making it difficult to meet the clinical need for accurate prediction of efficacy in malignant tumors.
An improved deep convolutional neural network is used for feature extraction. Combined with multi-region classification and binarization modules, an 11-dimensional structured index system is constructed. Through parallel prediction of multiple models, accurate identification and combined feature prediction of tumor, necrosis and lymphatic infiltration areas are achieved.
It provides an objective, accurate, and interpretable assessment tool that can systematically analyze the spatial combination patterns of tumor, necrosis, and lymphatic infiltration areas, supporting the efficacy assessment after neoadjuvant therapy and overcoming the subjectivity and limitations of traditional assessment methods.
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