TY - JOUR
T1 - Promises of big data and artificial intelligence in nephrology and transplantation
AU - Thongprayoon, Charat
AU - Kaewput, Wisit
AU - Kovvuru, Karthik
AU - Hansrivijit, Panupong
AU - Kanduri, Swetha R.
AU - Bathini, Tarun
AU - Chewcharat, Api
AU - Leeaphorn, Napat
AU - Gonzalez-Suarez, Maria L.
AU - Cheungpasitporn, Wisit
N1 - Publisher Copyright:
© 2020 by the authors. Licensee MDPI, Basel, Switzerland.
PY - 2020/4
Y1 - 2020/4
N2 - 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.
AB - 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.
KW - Acute kidney injury
KW - Artificial intelligence
KW - Big data
KW - Chronic kidney disease
KW - Kidney transplantation
KW - Machine learning
KW - Nephrology
KW - Transplantation
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U2 - 10.3390/jcm9041107
DO - 10.3390/jcm9041107
M3 - Editorial
AN - SCOPUS:85085195723
SN - 2077-0383
VL - 9
JO - Journal of Clinical Medicine
JF - Journal of Clinical Medicine
IS - 4
M1 - 1107
ER -