基于人工智能的数字图像饮食评估方法与人类和地面实况的比较:系统综述

IF 4.9 2区 医学 Q1 MEDICINE, GENERAL & INTERNAL
Eleanor Shonkoff, Kelly Copeland Cara, Xuechen (Anna) Pei, Mei Chung, Shreyas Kamath, Karen Panetta, Erin Hennessy
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引用次数: 0

摘要

人为错误估计食物摄入量是造成营养研究偏差的主要原因。人工智能(AI)方法可以减少偏差,但人工智能估计的总体准确性尚不清楚。本研究...
本文章由计算机程序翻译,如有差异,请以英文原文为准。
AI-based digital image dietary assessment methods compared to humans and ground truth: a systematic review
Human error estimating food intake is a major source of bias in nutrition research. Artificial intelligence (AI) methods may reduce bias, but the overall accuracy of AI estimates is unknown. This s...
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来源期刊
Annals of medicine
Annals of medicine 医学-医学:内科
CiteScore
4.90
自引率
0.00%
发文量
292
审稿时长
3 months
期刊介绍: Annals of Medicine is one of the world’s leading general medical review journals, boasting an impact factor of 5.435. It presents high-quality topical review articles, commissioned by the Editors and Editorial Committee, as well as original articles. The journal provides the current opinion on recent developments across the major medical specialties, with a particular focus on internal medicine. The peer-reviewed content of the journal keeps readers updated on the latest advances in the understanding of the pathogenesis of diseases, and in how molecular medicine and genetics can be applied in daily clinical practice.
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