Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.

ABSTRACT:

Background

Most patients with multiple hepatocellular carcinoma (MHCC) are at advanced stage once diagnosed, so that clinical treatment and decision-making are quite tricky. The AJCC-TNM system cannot accurately determine prognosis, our study aimed to identify prognostic factors for MHCC and to develop a prognostic model to quantify the risk and survival probability of patients.

Methods

Eligible patients with HCC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and then prognostic models were built using Cox regression, machine learning (ML), and deep learning (DL) algorithms. The model's performance was evaluated using C-index, receiver operating characteristic curve, Brier score and decision curve analysis, respectively, and the best mode

SUBMITTER: Shen J 

PROVIDER: S-EPMC11466773 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature