Machine-learning analysis of contrast-enhanced CT radiomics predicts recurrence of hepatocellular carcinoma after resection: A multi-institutional study.
Journal:
EBioMedicine
PMID:
31735556
Abstract
BACKGROUND: Current guidelines recommend surgical resection as the first-line option for patients with solitary hepatocellular carcinoma (HCC); unfortunately, postoperative recurrence rate remains high and there is no reliable prediction tool. We explored the potential of radiomics coupled with machine-learning algorithms to improve the predictive accuracy for HCC recurrence.
Authors
Keywords
Algorithms
Carcinoma, Hepatocellular
Contrast Media
Female
Hepatectomy
Humans
Image Processing, Computer-Assisted
Liver Neoplasms
Machine Learning
Male
Neoplasm Recurrence, Local
Prognosis
Proportional Hazards Models
Radiographic Image Enhancement
Retrospective Studies
Tomography, X-Ray Computed
Workflow