Project title
整合代謝體學、蛋白質體學和人工智慧以早期診斷胰臟癌
Internal ID
NSTC113-2923-B002-006-MY2
Principal Investigator
Start Date
October 1, 2024
End Date
September 30, 2025
Investigators
胡春美
Organizations
Partner Organizations
Integrating Metabolomics, Proteomics and Artificial Intelligence for Early Detection of Pancreatic Cancer
Keywords
Metabolomics
Proteomics
Artificial Intelligence
Pancreatic Cancer
Description
We propose a novel approach for PDAC detection in clinical applications, leveraging the combined power of metabolomics, proteomics, clinical data, biochemical biomarkers, and machine learning. This hybrid AI model will integrate diverse information layers, including metabolic and proteomic profiles, patient clinical parameters (age, gender, smoking status, BMI, HbA1c, or GluAC), and established PDAC markers, to achieve superior diagnostic accuracy and sensitivity compared to traditional methods. This integrated approach can potentially revolutionize PDAC detection, leading to earlier intervention and improved patient outcomes. Furthermore, the scientific findings of the project can undergo cross-validation in both Taiwan and Lithuania, suggesting their potential applicability worldwide to benefit diverse populations. Enhanced international cooperation among medical institutes could facilitate the validation of these results.