Development of an AI system for accurately diagnose hepatocellular carcinoma from computed tomography imaging data.

ABSTRACT:

Background and aims

Computed tomography (CT) scan is frequently used to detect hepatocellular carcinoma (HCC) in routine clinical practice. The aim of this study is to develop a deep-learning AI system to improve the diagnostic accuracy of HCC by analysing liver CT imaging data.

Methods

We developed a deep-learning AI system by training on CT images from 7512 patients at Henan Provincial Peoples' Hospital. Its performance was validated on one internal test set (Henan Provincial Peoples' Hospital, n = 385) and one external test set (Henan Provincial Cancer Hospital, n = 556). The area under the receiver-operating characteristic curve (AUROC) was used as the primary classification metric. Accuracy, sensitivity, specificity, precision, negative predictive value and F1 metric we

SUBMITTER: Wang M 

PROVIDER: S-EPMC8505513 | biostudies-literature | 2021 Oct

REPOSITORIES: biostudies-literature