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Precision medicine in the era of artificial intelligence: implications in chronic disease management
Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflammatory pathway. Inflammation is the natural reactio...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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BioMed Central
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725219/ https://www.ncbi.nlm.nih.gov/pubmed/33298113 http://dx.doi.org/10.1186/s12967-020-02658-5 |
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author | Subramanian, Murugan Wojtusciszyn, Anne Favre, Lucie Boughorbel, Sabri Shan, Jingxuan Letaief, Khaled B. Pitteloud, Nelly Chouchane, Lotfi |
author_facet | Subramanian, Murugan Wojtusciszyn, Anne Favre, Lucie Boughorbel, Sabri Shan, Jingxuan Letaief, Khaled B. Pitteloud, Nelly Chouchane, Lotfi |
author_sort | Subramanian, Murugan |
collection | PubMed |
description | Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflammatory pathway. Inflammation is the natural reaction of the immune system to a variety of stimuli, such as pathogens, damaged cells, and harmful substances. Metabolically triggered inflammation, also called metaflammation or low-grade chronic inflammation, is the consequence of a synergic interaction between the host and the exposome—a combination of environmental drivers, including diet, lifestyle, pollutants and other factors throughout the life span of an individual. Various levels of chronic inflammation are associated with several lifestyle-related diseases such as diabetes, obesity, metabolic associated fatty liver disease (MAFLD), cancers, cardiovascular disorders (CVDs), autoimmune diseases, and chronic lung diseases. Chronic diseases are a growing concern worldwide, placing a heavy burden on individuals, families, governments, and health-care systems. New strategies are needed to empower communities worldwide to prevent and treat these diseases. Precision medicine provides a model for the next generation of lifestyle modification. This will capitalize on the dynamic interaction between an individual’s biology, lifestyle, behavior, and environment. The aim of precision medicine is to design and improve diagnosis, therapeutics and prognostication through the use of large complex datasets that incorporate individual gene, function, and environmental variations. The implementation of high-performance computing (HPC) and artificial intelligence (AI) can predict risks with greater accuracy based on available multidimensional clinical and biological datasets. AI-powered precision medicine provides clinicians with an opportunity to specifically tailor early interventions to each individual. In this article, we discuss the strengths and limitations of existing and evolving recent, data-driven technologies, such as AI, in preventing, treating and reversing lifestyle-related diseases. |
format | Online Article Text |
id | pubmed-7725219 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-77252192020-12-10 Precision medicine in the era of artificial intelligence: implications in chronic disease management Subramanian, Murugan Wojtusciszyn, Anne Favre, Lucie Boughorbel, Sabri Shan, Jingxuan Letaief, Khaled B. Pitteloud, Nelly Chouchane, Lotfi J Transl Med Review Aberrant metabolism is the root cause of several serious health issues, creating a huge burden to health and leading to diminished life expectancy. A dysregulated metabolism induces the secretion of several molecules which in turn trigger the inflammatory pathway. Inflammation is the natural reaction of the immune system to a variety of stimuli, such as pathogens, damaged cells, and harmful substances. Metabolically triggered inflammation, also called metaflammation or low-grade chronic inflammation, is the consequence of a synergic interaction between the host and the exposome—a combination of environmental drivers, including diet, lifestyle, pollutants and other factors throughout the life span of an individual. Various levels of chronic inflammation are associated with several lifestyle-related diseases such as diabetes, obesity, metabolic associated fatty liver disease (MAFLD), cancers, cardiovascular disorders (CVDs), autoimmune diseases, and chronic lung diseases. Chronic diseases are a growing concern worldwide, placing a heavy burden on individuals, families, governments, and health-care systems. New strategies are needed to empower communities worldwide to prevent and treat these diseases. Precision medicine provides a model for the next generation of lifestyle modification. This will capitalize on the dynamic interaction between an individual’s biology, lifestyle, behavior, and environment. The aim of precision medicine is to design and improve diagnosis, therapeutics and prognostication through the use of large complex datasets that incorporate individual gene, function, and environmental variations. The implementation of high-performance computing (HPC) and artificial intelligence (AI) can predict risks with greater accuracy based on available multidimensional clinical and biological datasets. AI-powered precision medicine provides clinicians with an opportunity to specifically tailor early interventions to each individual. In this article, we discuss the strengths and limitations of existing and evolving recent, data-driven technologies, such as AI, in preventing, treating and reversing lifestyle-related diseases. BioMed Central 2020-12-09 /pmc/articles/PMC7725219/ /pubmed/33298113 http://dx.doi.org/10.1186/s12967-020-02658-5 Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Review Subramanian, Murugan Wojtusciszyn, Anne Favre, Lucie Boughorbel, Sabri Shan, Jingxuan Letaief, Khaled B. Pitteloud, Nelly Chouchane, Lotfi Precision medicine in the era of artificial intelligence: implications in chronic disease management |
title | Precision medicine in the era of artificial intelligence: implications in chronic disease management |
title_full | Precision medicine in the era of artificial intelligence: implications in chronic disease management |
title_fullStr | Precision medicine in the era of artificial intelligence: implications in chronic disease management |
title_full_unstemmed | Precision medicine in the era of artificial intelligence: implications in chronic disease management |
title_short | Precision medicine in the era of artificial intelligence: implications in chronic disease management |
title_sort | precision medicine in the era of artificial intelligence: implications in chronic disease management |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7725219/ https://www.ncbi.nlm.nih.gov/pubmed/33298113 http://dx.doi.org/10.1186/s12967-020-02658-5 |
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