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Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation
Data has always been integral to modern medicine in almost all aspects of patient care and the recent proliferation of data has opened up innumerable opportunities for all the stakeholders in trying to improve the quality of care and health outcomes including quality of life and rehabilitation. Grea...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863295/ https://www.ncbi.nlm.nih.gov/pubmed/35193536 http://dx.doi.org/10.1186/s12891-022-05126-x |
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author | Kataria, Suchitra Ravindran, Vinod |
author_facet | Kataria, Suchitra Ravindran, Vinod |
author_sort | Kataria, Suchitra |
collection | PubMed |
description | Data has always been integral to modern medicine in almost all aspects of patient care and the recent proliferation of data has opened up innumerable opportunities for all the stakeholders in trying to improve the quality of care and health outcomes including quality of life and rehabilitation. Greater usage and adoption of digital technologies have led to the convergence of health data in different forms – clinical, self-reported, electronic health records social media, etc. The application and utilization of patient data set continue to get broadened each day with greater availability and access. These are empowering newer cutting-edge solutions such as connected care and artificial intelligence, 3D printing and real-life mimicking prosthetics. The availability of data at micro and macro levels has the potential to act as a catalyst for personalized care based on behavioral, cultural, genetic, and psychological needs for patients with musculoskeletal disorders. Realistic algorithms coupled with biomarkers which can identify relevant interventions and alert the care providers regarding any deterioration. Although in the nascent stage currently, 3D printing, exoskeletons, and virtual rehabilitation hold tremendous potential of cost-effective, precise interventions for the patients. |
format | Online Article Text |
id | pubmed-8863295 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-88632952022-02-23 Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation Kataria, Suchitra Ravindran, Vinod BMC Musculoskelet Disord Review Data has always been integral to modern medicine in almost all aspects of patient care and the recent proliferation of data has opened up innumerable opportunities for all the stakeholders in trying to improve the quality of care and health outcomes including quality of life and rehabilitation. Greater usage and adoption of digital technologies have led to the convergence of health data in different forms – clinical, self-reported, electronic health records social media, etc. The application and utilization of patient data set continue to get broadened each day with greater availability and access. These are empowering newer cutting-edge solutions such as connected care and artificial intelligence, 3D printing and real-life mimicking prosthetics. The availability of data at micro and macro levels has the potential to act as a catalyst for personalized care based on behavioral, cultural, genetic, and psychological needs for patients with musculoskeletal disorders. Realistic algorithms coupled with biomarkers which can identify relevant interventions and alert the care providers regarding any deterioration. Although in the nascent stage currently, 3D printing, exoskeletons, and virtual rehabilitation hold tremendous potential of cost-effective, precise interventions for the patients. BioMed Central 2022-02-22 /pmc/articles/PMC8863295/ /pubmed/35193536 http://dx.doi.org/10.1186/s12891-022-05126-x Text en © The Author(s) 2022 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/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://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 Kataria, Suchitra Ravindran, Vinod Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
title | Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
title_full | Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
title_fullStr | Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
title_full_unstemmed | Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
title_short | Musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
title_sort | musculoskeletal care – at the confluence of data science, sensors, engineering, and computation |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8863295/ https://www.ncbi.nlm.nih.gov/pubmed/35193536 http://dx.doi.org/10.1186/s12891-022-05126-x |
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