Published online Oct 28, 2022. doi: 10.35712/aig.v3.i4.105
Peer-review started: June 22, 2022
First decision: July 11, 2022
Revised: July 13, 2022
Accepted: October 26, 2022
Article in press: October 26, 2022
Published online: October 28, 2022
About 25% of the general population in Japan are reported to have nonalcoholic fatty liver disease (NAFLD). NAFLD and nonalcoholic steatohepatitis carry a risk of progressing further to hepatocellular carcinoma. The primary treatment for NAFLD is dietary therapy. Dietary counseling plays an essential role in dietary therapy. Although artificial intelligence (AI)-based nutrition management software applications have been developed and put into practical use in recent years, the majority focus on weight loss or muscle strengthening, and no software has been developed for patient use in clinical practice.
To examine whether effective dietary counseling is possible using AI-based nutrition management software.
NAFLD patients who had been assessed using an AI-based nutrition management software application (Calomeal) that automatically analyzed images of meals photographed by patients and agreed to receive dietary counseling were given dietary counseling. Blood biochemistry tests were performed before (baseline) and 6 mo after (6M follow-up) dietary counseling. After the dietary counseling, the patients were asked to complete a questionnaire survey.
A total of 29 patients diagnosed with NAFLD between August 2020 and March 2022 were included. There were significant decreases in liver enzyme and triglyceride levels at the 6M follow-up compared to baseline. The food analysis capability of the AI used by Calomeal in this study was 75.1%. Patient satisfaction with the AI-based dietary counselling was high.
AI-based nutrition management appeared to raise awareness of dietary habits among NAFLD patients. However, it did not directly alleviate the burden of registered dietitians, and impro
Core Tip: Use of artificial intelligence (AI)-based nutrition management software (Calomeal) appeared to raise awareness of nonalcoholic fatty liver disease patients’ dietary habits, and they showed significant decreases in liver enzyme and triglyceride levels at the 6-mo follow-up compared to baseline. The food analysis capability of the AI package used in this study was 75.1%, and patient satisfaction with the AI-based dietary counselling was high. However, due to the limitations of the food analysis capabilities of AI, it did not directly alleviate the burden of registered dietitians, and improvements in the analytical capabilities of AI are much anticipated.