mediatto:使用人工智能来评估和改善地中海饮食依从性

Arindam Ghosh
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引用次数: 1

摘要

许多研究已经证明地中海饮食坚持(MDA)在改善长期减肥结果、心血管健康和减少糖尿病患者并发症方面的益处。然而,定期对MDA进行人工评估是具有挑战性的,需要一种方便的评估方法来进行大规模采用。mediPiatto研究项目的目标是开发一个基于人工智能的端到端自动系统,用于从膳食日志图像中评估和改进MDA。开发的系统被嵌入到一个智能手机应用程序中,用于膳食跟踪。对24名参与者进行了为期4周的可行性研究,并向他们发送了一份每周报告,其中包含量化他们遵守情况的分数。四名用户的系统生成的MDA评分与一位专家营养师计算的MDA评分相比,平均差异为3.5%。一份自我报告的食物频率问卷(FFQ)——用来衡量一个人遵守饮食习惯的自我测量——显示,在研究期间,24名参与者中有19人的得分总体上有所提高。一项研究结束后的调查显示,24名参与者中有20人表示他们对将该系统纳入日常生活感兴趣,总体上得到了积极的反馈。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
mediPiatto: Using AI to Assess and Improve Mediterranean Diet Adherence
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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