Improving Multi-Tumor Biomarker Health Check-up Tests with Machine Learning Algorithms.

ABSTRACT: Tumor markers are used to screen tens of millions of individuals worldwide at annual health check-ups, especially in East Asia. Machine learning (ML)-based algorithms that improve the diagnostic accuracy and clinical utility of these tests can have substantial impact leading to the early diagnosis of cancer. ML-based algorithms, including a cancer screening algorithm and a secondary organ of origin algorithm, were developed and validated using a large real world dataset (RWD) from asymptomatic individuals undergoing routine cancer screening at a Taiwanese medical center between May 2001 and April 2015. External validation was performed using data from the same period from a separate medical center. The data set included tumor marker values, age, and gender from 27,938 individuals, includin

SUBMITTER: Wang HY 

PROVIDER: S-EPMC7352838 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature