36. Development of a Software Support System for Targeted Treatment of Non-Small Cell Lung Cancer Utilizing Genetic Mutation Analysis Data
Nội dung chính của bài viết
Tóm tắt
This study presents the development of a software support system aimed at improving targeted treatment outcomes in non-small cell lung cancer (NSCLC) by utilizing genetic mutation analysis data. PubMed BERT model were generated to identify tumor gene mutated features associated with gene-drug responses. Then the best classifier with highest accuracy served for the development of the support software. A multi-center retrospective cohort study was conducted to evaluate of treatment outcomes based on software support to identify and predict targeted therapeutic in NSCLC. The results demonstrated the potential of leveraging genetic mutation analysis data and AI technology to optimize treatment strategies and improve outcomes for NSCLC patients with PubMed BERT model in extracting and categorizing keywords to build the database (a Recall (sensitivity) score of 98.12%). The study revealed that among the 109 patients with EGFR mutations identified through NGS analysis, 72% showed partial responsiveness, overall response rate (ORR) was 67.0%, and the disease control rate (DCR) was 82.6%. The software support system developed in this study holds promise for enhancing personalized treatment approaches in NSCLC by leveraging genetic mutation analysis data to guide targeted therapies and improve the treatment outcome for patients.
Chi tiết bài viết
Từ khóa
Supported software; Targeted therapy, EGFR, Lung cancer
Tài liệu tham khảo
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