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The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition
PURPOSE OF REVIEW: Computing advances over the decades have catalyzed the pervasive integration of digital technology in the medical industry, now followed by similar applications for clinical nutrition. This review discusses the implementation of such technologies for nutrition, ranging from the us...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer US
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8186363/ https://www.ncbi.nlm.nih.gov/pubmed/34123579 http://dx.doi.org/10.1007/s40137-021-00297-3 |
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author | Limketkai, Berkeley N. Mauldin, Kasuen Manitius, Natalie Jalilian, Laleh Salonen, Bradley R. |
author_facet | Limketkai, Berkeley N. Mauldin, Kasuen Manitius, Natalie Jalilian, Laleh Salonen, Bradley R. |
author_sort | Limketkai, Berkeley N. |
collection | PubMed |
description | PURPOSE OF REVIEW: Computing advances over the decades have catalyzed the pervasive integration of digital technology in the medical industry, now followed by similar applications for clinical nutrition. This review discusses the implementation of such technologies for nutrition, ranging from the use of mobile apps and wearable technologies to the development of decision support tools for parenteral nutrition and use of telehealth for remote assessment of nutrition. RECENT FINDINGS: Mobile applications and wearable technologies have provided opportunities for real-time collection of granular nutrition-related data. Machine learning has allowed for more complex analyses of the increasing volume of data collected. The combination of these tools has also translated into practical clinical applications, such as decision support tools, risk prediction, and diet optimization. SUMMARY: The state of digital technology for clinical nutrition is still young, although there is much promise for growth and disruption in the future. |
format | Online Article Text |
id | pubmed-8186363 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Springer US |
record_format | MEDLINE/PubMed |
spelling | pubmed-81863632021-06-09 The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition Limketkai, Berkeley N. Mauldin, Kasuen Manitius, Natalie Jalilian, Laleh Salonen, Bradley R. Curr Surg Rep Nutrition, Metabolism, and Surgery (K Miller, Section Editor) PURPOSE OF REVIEW: Computing advances over the decades have catalyzed the pervasive integration of digital technology in the medical industry, now followed by similar applications for clinical nutrition. This review discusses the implementation of such technologies for nutrition, ranging from the use of mobile apps and wearable technologies to the development of decision support tools for parenteral nutrition and use of telehealth for remote assessment of nutrition. RECENT FINDINGS: Mobile applications and wearable technologies have provided opportunities for real-time collection of granular nutrition-related data. Machine learning has allowed for more complex analyses of the increasing volume of data collected. The combination of these tools has also translated into practical clinical applications, such as decision support tools, risk prediction, and diet optimization. SUMMARY: The state of digital technology for clinical nutrition is still young, although there is much promise for growth and disruption in the future. Springer US 2021-06-08 2021 /pmc/articles/PMC8186363/ /pubmed/34123579 http://dx.doi.org/10.1007/s40137-021-00297-3 Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . |
spellingShingle | Nutrition, Metabolism, and Surgery (K Miller, Section Editor) Limketkai, Berkeley N. Mauldin, Kasuen Manitius, Natalie Jalilian, Laleh Salonen, Bradley R. The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition |
title | The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition |
title_full | The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition |
title_fullStr | The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition |
title_full_unstemmed | The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition |
title_short | The Age of Artificial Intelligence: Use of Digital Technology in Clinical Nutrition |
title_sort | age of artificial intelligence: use of digital technology in clinical nutrition |
topic | Nutrition, Metabolism, and Surgery (K Miller, Section Editor) |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8186363/ https://www.ncbi.nlm.nih.gov/pubmed/34123579 http://dx.doi.org/10.1007/s40137-021-00297-3 |
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