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Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation

Kidney diseases form part of the major health burdens experienced all over the world. Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great importance of collecting a large quantity of health-related data among human cohorts, what scholars refer to as “big data”,...

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Autores principales: Thongprayoon, Charat, Kaewput, Wisit, Kovvuru, Karthik, Hansrivijit, Panupong, Kanduri, Swetha R., Bathini, Tarun, Chewcharat, Api, Leeaphorn, Napat, Gonzalez-Suarez, Maria L., Cheungpasitporn, Wisit
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230205/
https://www.ncbi.nlm.nih.gov/pubmed/32294906
http://dx.doi.org/10.3390/jcm9041107
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author Thongprayoon, Charat
Kaewput, Wisit
Kovvuru, Karthik
Hansrivijit, Panupong
Kanduri, Swetha R.
Bathini, Tarun
Chewcharat, Api
Leeaphorn, Napat
Gonzalez-Suarez, Maria L.
Cheungpasitporn, Wisit
author_facet Thongprayoon, Charat
Kaewput, Wisit
Kovvuru, Karthik
Hansrivijit, Panupong
Kanduri, Swetha R.
Bathini, Tarun
Chewcharat, Api
Leeaphorn, Napat
Gonzalez-Suarez, Maria L.
Cheungpasitporn, Wisit
author_sort Thongprayoon, Charat
collection PubMed
description Kidney diseases form part of the major health burdens experienced all over the world. Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great importance of collecting a large quantity of health-related data among human cohorts, what scholars refer to as “big data”, has increasingly been identified, with the establishment of a large group of cohorts and the usage of electronic health records (EHRs) in nephrology and transplantation. These data are valuable, and can potentially be utilized by researchers to advance knowledge in the field. Furthermore, progress in big data is stimulating the flourishing of artificial intelligence (AI), which is an excellent tool for handling, and subsequently processing, a great amount of data and may be applied to highlight more information on the effectiveness of medicine in kidney-related complications for the purpose of more precise phenotype and outcome prediction. In this article, we discuss the advances and challenges in big data, the use of EHRs and AI, with great emphasis on the usage of nephrology and transplantation.
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spelling pubmed-72302052020-05-28 Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation Thongprayoon, Charat Kaewput, Wisit Kovvuru, Karthik Hansrivijit, Panupong Kanduri, Swetha R. Bathini, Tarun Chewcharat, Api Leeaphorn, Napat Gonzalez-Suarez, Maria L. Cheungpasitporn, Wisit J Clin Med Editorial Kidney diseases form part of the major health burdens experienced all over the world. Kidney diseases are linked to high economic burden, deaths, and morbidity rates. The great importance of collecting a large quantity of health-related data among human cohorts, what scholars refer to as “big data”, has increasingly been identified, with the establishment of a large group of cohorts and the usage of electronic health records (EHRs) in nephrology and transplantation. These data are valuable, and can potentially be utilized by researchers to advance knowledge in the field. Furthermore, progress in big data is stimulating the flourishing of artificial intelligence (AI), which is an excellent tool for handling, and subsequently processing, a great amount of data and may be applied to highlight more information on the effectiveness of medicine in kidney-related complications for the purpose of more precise phenotype and outcome prediction. In this article, we discuss the advances and challenges in big data, the use of EHRs and AI, with great emphasis on the usage of nephrology and transplantation. MDPI 2020-04-13 /pmc/articles/PMC7230205/ /pubmed/32294906 http://dx.doi.org/10.3390/jcm9041107 Text en © 2020 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 Editorial
Thongprayoon, Charat
Kaewput, Wisit
Kovvuru, Karthik
Hansrivijit, Panupong
Kanduri, Swetha R.
Bathini, Tarun
Chewcharat, Api
Leeaphorn, Napat
Gonzalez-Suarez, Maria L.
Cheungpasitporn, Wisit
Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation
title Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation
title_full Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation
title_fullStr Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation
title_full_unstemmed Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation
title_short Promises of Big Data and Artificial Intelligence in Nephrology and Transplantation
title_sort promises of big data and artificial intelligence in nephrology and transplantation
topic Editorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7230205/
https://www.ncbi.nlm.nih.gov/pubmed/32294906
http://dx.doi.org/10.3390/jcm9041107
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