Application of a deep learning algorithm for the diagnosis of HCC.

ABSTRACT:

Background & aims

Hepatocellular carcinoma (HCC) is characterized by a high mortality rate. The Liver Imaging Reporting and Data System (LI-RADS) results in a considerable number of indeterminate observations, rendering an accurate diagnosis difficult.

Methods

We developed four deep learning models for diagnosing HCC on computed tomography (CT) via a training-validation-testing approach. Thin-slice triphasic CT liver images and relevant clinical information were collected and processed for deep learning. HCC was diagnosed and verified via a 12-month clinical composite reference standard. CT observations among at-risk patients were annotated using LI-RADS. Diagnostic performance was assessed by internal validation and independent external testing. We conducted sensitivity ana

SUBMITTER: Yu PLH 

PROVIDER: S-EPMC11648772 | biostudies-literature | 2025 Jan

REPOSITORIES: biostudies-literature