地中海饮食法
餐食
医学
减肥
跟踪(教育)
物理疗法
内科学
心理学
肥胖
教育学
标识
DOI:10.1145/3552484.3554368
摘要
Numerous studies have demonstrated the benefits of Mediterranean Diet Adherence (MDA) to improved long-term weight loss outcomes, positive effects on cardiovascular health, and decrease in complications among diabetic patients. However, manual assessment of MDA on a regular basis is challenging, and a convenient method of such evaluation is needed for mass adoption. The goal of the mediPiatto research project was to develop an AI-based end-to-end automatic system for evaluation and improvement of MDA from meal log images. The developed system was embedded into a smartphone application for meal tracking. A 4-week feasibility study was conducted with 24 participants where a weekly report with a score quantifying their adherence was sent to them. A comparison of the system-generated MDA score of four users with that calculated by an expert dietitian showed a mean difference of 3.5%. A self-reported food frequency questionnaire (FFQ) - used as a self-measurement of a person's compliance with the MD - showed that 19 out of 24 participants had an overall increase in the score over the period of the study. An end-of-study survey yielded overall positive feedback from the participants with 20 out of 24 reporting that they would be interested in incorporating the system in their daily lives.
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