Deep learning-based identification of patients at increased risk of cancer using routine laboratory markers.

ABSTRACT: Early screening for cancer has proven to improve the survival rate and spare patients from intensive and costly treatments due to late diagnosis. Cancer screening in the healthy population involves an initial risk stratification step to determine the screening method and frequency, primarily to optimize resource allocation by targeting screening towards individuals who draw most benefit. For most screening programs, age and clinical risk factors such as family history are part of the initial risk stratification algorithm. In this paper, we focus on developing a blood marker-based risk stratification approach, which could be used to identify patients with elevated cancer risk to be encouraged for taking a diagnostic test or participate in a screening program. We demonstrate that the combina

SUBMITTER: Singh V 

PROVIDER: S-EPMC11993759 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature