Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review
المؤلفون المشاركون
Burlacu, Alexandru
Iftene, Adrian
Jugrin, Daniel
Popa, Iolanda Valentina
Lupu, Paula Madalina
Vlad, Cristiana
Covic, Adrian
المصدر
العدد
المجلد 2020، العدد 2020 (31 ديسمبر/كانون الأول 2020)، ص ص. 1-14، 14ص.
الناشر
Hindawi Publishing Corporation
تاريخ النشر
2020-06-10
دولة النشر
مصر
عدد الصفحات
14
التخصصات الرئيسية
الملخص EN
Background.
The purpose of this review is to depict current research and impact of artificial intelligence/machine learning (AI/ML) algorithms on dialysis and kidney transplantation.
Published studies were presented from two points of view: What medical aspects were covered? What AI/ML algorithms have been used? Methods.
We searched four electronic databases or studies that used AI/ML in hemodialysis (HD), peritoneal dialysis (PD), and kidney transplantation (KT).
Sixty-nine studies were split into three categories: AI/ML and HD, PD, and KT, respectively.
We identified 43 trials in the first group, 8 in the second, and 18 in the third.
Then, studies were classified according to the type of algorithm.
Results.
AI and HD trials covered: (a) dialysis service management, (b) dialysis procedure, (c) anemia management, (d) hormonal/dietary issues, and (e) arteriovenous fistula assessment.
PD studies were divided into (a) peritoneal technique issues, (b) infections, and (c) cardiovascular event prediction.
AI in transplantation studies were allocated into (a) management systems (ML used as pretransplant organ-matching tools), (b) predicting graft rejection, (c) tacrolimus therapy modulation, and (d) dietary issues.
Conclusions.
Although guidelines are reluctant to recommend AI implementation in daily practice, there is plenty of evidence that AI/ML algorithms can predict better than nephrologists: volumes, Kt/V, and hypotension or cardiovascular events during dialysis.
Altogether, these trials report a robust impact of AI/ML on quality of life and survival in G5D/T patients.
In the coming years, one would probably witness the emergence of AI/ML devices that facilitate the management of dialysis patients, thus increasing the quality of life and survival.
نمط استشهاد جمعية علماء النفس الأمريكية (APA)
Burlacu, Alexandru& Iftene, Adrian& Jugrin, Daniel& Popa, Iolanda Valentina& Lupu, Paula Madalina& Vlad, Cristiana…[et al.]. 2020. Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review. BioMed Research International،Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1138335
نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)
Burlacu, Alexandru…[et al.]. Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review. BioMed Research International No. 2020 (2020), pp.1-14.
https://search.emarefa.net/detail/BIM-1138335
نمط استشهاد الجمعية الطبية الأمريكية (AMA)
Burlacu, Alexandru& Iftene, Adrian& Jugrin, Daniel& Popa, Iolanda Valentina& Lupu, Paula Madalina& Vlad, Cristiana…[et al.]. Using Artificial Intelligence Resources in Dialysis and Kidney Transplant Patients: A Literature Review. BioMed Research International. 2020. Vol. 2020, no. 2020, pp.1-14.
https://search.emarefa.net/detail/BIM-1138335
نوع البيانات
مقالات
لغة النص
الإنجليزية
الملاحظات
Includes bibliographical references
رقم السجل
BIM-1138335
قاعدة معامل التأثير والاستشهادات المرجعية العربي "ارسيف Arcif"
أضخم قاعدة بيانات عربية للاستشهادات المرجعية للمجلات العلمية المحكمة الصادرة في العالم العربي
تقوم هذه الخدمة بالتحقق من التشابه أو الانتحال في الأبحاث والمقالات العلمية والأطروحات الجامعية والكتب والأبحاث باللغة العربية، وتحديد درجة التشابه أو أصالة الأعمال البحثية وحماية ملكيتها الفكرية. تعرف اكثر