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AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity

Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be...

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Autores principales: Majnarić, Ljiljana Trtica, Babič, František, O’Sullivan, Shane, Holzinger, Andreas
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918668/
https://www.ncbi.nlm.nih.gov/pubmed/33672914
http://dx.doi.org/10.3390/jcm10040766
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author Majnarić, Ljiljana Trtica
Babič, František
O’Sullivan, Shane
Holzinger, Andreas
author_facet Majnarić, Ljiljana Trtica
Babič, František
O’Sullivan, Shane
Holzinger, Andreas
author_sort Majnarić, Ljiljana Trtica
collection PubMed
description Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be tailored to a single disease. To improve clinical decision making and patient care in multimorbidity, a radical change in the problem-solving approach to medical research and treatment is needed. In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity. This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors. However, to realize the idea of this paradigm shift in multimorbidity research, the optimization, standardization, and most importantly, the integration of electronic health data into a common national and international research infrastructure is needed. Ultimately, there is a need for the integration and implementation of efficient AI approaches, particularly deep learning, into clinical routine directly within the workflows of the medical professionals.
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spelling pubmed-79186682021-03-02 AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity Majnarić, Ljiljana Trtica Babič, František O’Sullivan, Shane Holzinger, Andreas J Clin Med Review Multimorbidity refers to the coexistence of two or more chronic diseases in one person. Therefore, patients with multimorbidity have multiple and special care needs. However, in practice it is difficult to meet these needs because the organizational processes of current healthcare systems tend to be tailored to a single disease. To improve clinical decision making and patient care in multimorbidity, a radical change in the problem-solving approach to medical research and treatment is needed. In addition to the traditional reductionist approach, we propose interactive research supported by artificial intelligence (AI) and advanced big data analytics. Such research approach, when applied to data routinely collected in healthcare settings, provides an integrated platform for research tasks related to multimorbidity. This may include, for example, prediction, correlation, and classification problems based on multiple interaction factors. However, to realize the idea of this paradigm shift in multimorbidity research, the optimization, standardization, and most importantly, the integration of electronic health data into a common national and international research infrastructure is needed. Ultimately, there is a need for the integration and implementation of efficient AI approaches, particularly deep learning, into clinical routine directly within the workflows of the medical professionals. MDPI 2021-02-14 /pmc/articles/PMC7918668/ /pubmed/33672914 http://dx.doi.org/10.3390/jcm10040766 Text en © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Majnarić, Ljiljana Trtica
Babič, František
O’Sullivan, Shane
Holzinger, Andreas
AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
title AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
title_full AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
title_fullStr AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
title_full_unstemmed AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
title_short AI and Big Data in Healthcare: Towards a More Comprehensive Research Framework for Multimorbidity
title_sort ai and big data in healthcare: towards a more comprehensive research framework for multimorbidity
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7918668/
https://www.ncbi.nlm.nih.gov/pubmed/33672914
http://dx.doi.org/10.3390/jcm10040766
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