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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”,...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7230205 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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