Cost-effectiveness analysis of the artificial intelligence diagnosis support system for early gastric cancers.

ABSTRACT:

Objectives

The introduction of artificial intelligence into the medical field has improved the diagnostic capabilities of physicians. However, few studies have analyzed the economic impact of employing artificial intelligence technologies in the clinical environment. This study evaluated the cost-effectiveness of a computer-assisted diagnosis (CADx) system designed to support clinicians in differentiating early gastric cancers from non-cancerous lesions in Japan, where the universal health insurance system was introduced.

Methods

The target population to be used for the CADx was estimated as those with moderate to severe gastritis caused by Helicobacter pylori infection. Decision trees with Markov models were built to analyze the cumulative cost-effectiveness of using

SUBMITTER: Yonazu S 

PROVIDER: S-EPMC10461711 | biostudies-literature | 2024 Apr

REPOSITORIES: biostudies-literature