Construction of a Disease-Syndrome Integrated Diagnosis and Treatment System for Gastric "Inflammation-Cancer" Transformation Based on Multi-Modal Phenotypic Modeling
|更新时间:2025-03-06
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Construction of a Disease-Syndrome Integrated Diagnosis and Treatment System for Gastric "Inflammation-Cancer" Transformation Based on Multi-Modal Phenotypic Modeling
Journal of Traditional Chinese MedicineVol. 66, Issue 5, Pages: 458-463(2025)
LI Hao,ZHANG Huiyao,BAI Wei,et al.Construction of a Disease-Syndrome Integrated Diagnosis and Treatment System for Gastric "Inflammation-Cancer" Transformation Based on Multi-Modal Phenotypic Modeling[J].Journal of Traditional Chinese Medicine,2025,66(05):458-463.
LI Hao,ZHANG Huiyao,BAI Wei,et al.Construction of a Disease-Syndrome Integrated Diagnosis and Treatment System for Gastric "Inflammation-Cancer" Transformation Based on Multi-Modal Phenotypic Modeling[J].Journal of Traditional Chinese Medicine,2025,66(05):458-463.DOI: 10.13288/j.11-2166/r.2025.05.005.
Construction of a Disease-Syndrome Integrated Diagnosis and Treatment System for Gastric "Inflammation-Cancer" Transformation Based on Multi-Modal Phenotypic Modeling
By analyzing the current application of multi-modal data in the diagnosis of gastric "inflammation-cancer" transformation, this study explored the feasibility and strategies for constructing a disease-syndrome integrated diagnosis and treatment system. Based on traditional Chinese medicine (TCM) phenomics, we proposed utilizing multi-modal data from literature research, cross-sectional studies, and cohort follow-ups, combined with artificial intelligence technology, to establish a multi-dimensional diagnostic and treatment index system. This approach aims to uncover the complex pathogenesis and transformation patterns of gastric "inflammation-cancer" progression. Additionally, by dynamically collecting TCM four-diagnostic information and modern medical diagnostic information through a long-term follow-up system, we developed three major modules including information extraction, multi-modal phenotypic modeling, and information output, to make it enable real-world clinical data-driven long-term follow-up and treatment of chronic atrophic gastritis. This system can provide technical support for clinical diagnosis, treatment evaluation, and research, while also offering insights and methods for intelligent TCM diagnosis.
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