Validation of a Deep Learning-Based Model to Predict Lung Cancer Risk Using Chest Radiographs and Electronic Medical Record Data.

ABSTRACT:

Importance

Lung cancer screening with chest computed tomography (CT) prevents lung cancer death; however, fewer than 5% of eligible Americans are screened. CXR-LC, an open-source deep learning tool that estimates lung cancer risk from existing chest radiograph images and commonly available electronic medical record (EMR) data, may enable automated identification of high-risk patients as a step toward improving lung cancer screening participation.

Objective

To validate CXR-LC using EMR data to identify individuals at high-risk for lung cancer to complement 2022 US Centers for Medicare & Medicaid Services (CMS) lung cancer screening eligibility guidelines.

Design, setting, and participants

This prognostic study compared CXR-LC estimates with CMS screening guidelines usi

SUBMITTER: Raghu VK 

PROVIDER: S-EPMC9857639 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature