Artificial Intelligence Applications in Digital Anthropometry OBM integrative and complimentary medicine Pub Date : 2022-12-26 DOI:10.21926/obm.icm.2204056 D. Bonilla 求助PDF {"title":"Artificial Intelligence Applications in Digital Anthropometry <sup><a class=\"tippyShow\" data-tippy-arrow=\"true\"data-tippy-content=\"Presented as a keynote at the 'I Congreso Iberoamericano de Antropometría Aplicada' organized by the 'Red Iberoamericana de Investigadores en Antropometría Aplicada'.\" d","authors":"D. Bonilla","doi":"10.21926/obm.icm.2204056","DOIUrl":null,"url":null,"abstract":"Anthropometric measurements are frequently used to assess changes in body composition in different populations. Despite being a cheap, in-field, and relatively valid technique, the COVID-19 pandemic has impulse research on digital anthropometry across the globe. Machine learning, as the convergence of artificial intelligence and data mining, has the potential to improve data collection and analysis in the applications of kinanthropometry. Far from replacing conventional methods, digital anthropometry is a powerful opportunity to increase accuracy, validity, practicality, and the use of self-monitoring procedures under professional supervision. However, further research and scientific literacy among practitioners are warranted.","PeriodicalId":74333,"journal":{"name":"OBM integrative and complimentary medicine","volume":" ","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2022-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"OBM integrative and complimentary medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.21926/obm.icm.2204056","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0} 引用次数: 0 引用 批量引用 Abstract Anthropometric measurements are frequently used to assess changes in body composition in different populations. Despite being a cheap, in-field, and relatively valid technique, the COVID-19 pandemic has impulse research on digital anthropometry across the globe. Machine learning, as the convergence of artificial intelligence and data mining, has the potential to improve data collection and analysis in the applications of kinanthropometry. Far from replacing conventional methods, digital anthropometry is a powerful opportunity to increase accuracy, validity, practicality, and the use of self-monitoring procedures under professional supervision. However, further research and scientific literacy among practitioners are warranted. 分享 查看原文 本刊更多论文 人工智能在数字人类学中的应用 人体测量常用于评估不同人群身体成分的变化。尽管这是一种廉价、实地且相对有效的技术，但COVID-19大流行推动了全球对数字人体测量学的研究。机器学习作为人工智能和数据挖掘的融合，有可能改善人体测量学应用中的数据收集和分析。数字人体测量远没有取代传统的方法，它是一个强大的机会，可以提高准确性、有效性、实用性，并在专业监督下使用自我监测程序。然而，进一步的研究和从业者的科学素养是有必要的。 本文章由计算机程序翻译，如有差异，请以英文原文为准。

Abstract

Anthropometric measurements are frequently used to assess changes in body composition in different populations. Despite being a cheap, in-field, and relatively valid technique, the COVID-19 pandemic has impulse research on digital anthropometry across the globe. Machine learning, as the convergence of artificial intelligence and data mining, has the potential to improve data collection and analysis in the applications of kinanthropometry. Far from replacing conventional methods, digital anthropometry is a powerful opportunity to increase accuracy, validity, practicality, and the use of self-monitoring procedures under professional supervision. However, further research and scientific literacy among practitioners are warranted.