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ID 61534
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Ohara, Toshiaki Department of Pathology & Experimental Medicine, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences ORCID Kaken ID publons researchmap
Ikeda, Hiroshi Department of Internal Medicine, Shigei Medical Research Hospital
Sugitani, Yoshiki Advanced Institute for Materials Research, Tohoku University
Suito, Hiroshi Advanced Institute for Materials Research, Tohoku University ORCID Kaken ID publons researchmap
Huynh, Viet Quang Huy Advanced Institute for Materials Research, Tohoku University
Kinomura, Masaru Division of Hemodialysis and Apheresis, Okayama University Hospital
Haraguchi, Soichiro Kobayashi Medicine Clinic
Sakurama, Kazufumi Department of Gastroenterological Surgery, Okayama University Graduate School of Medicine, Dentistry and Pharmaceutical Sciences
Abstract
Anemia, for which erythropoiesis-stimulating agents (ESAs) and iron supplements (ISs) are used as preventive measures, presents important difficulties for hemodialysis patients. Nevertheless, the number of physicians able to manage such medications appropriately is not keeping pace with the rapid increase of hemodialysis patients. Moreover, the high cost of ESAs imposes heavy burdens on medical insurance systems. An artificial-intelligence-supported anemia control system (AISACS) trained using administration direction data from experienced physicians has been developed by the authors. For the system, appropriate data selection and rectification techniques play important roles. Decision making related to ESAs poses a multi-class classification problem for which a two-step classification technique is introduced. Several validations have demonstrated that AISACS exhibits high performance with correct classification rates of 72%-87% and clinically appropriate classification rates of 92%-98%.
Keywords
anemia
artificial intelligence
chronic kidney disease
erythropoiesis-stimulating agents
hemodialysis
iron
Published Date
2021-02-22
Publication Title
International Journal of Medical Sciences
Volume
volume18
Issue
issue8
Publisher
Ivyspring International Publisher
Start Page
1831
End Page
1839
ISSN
1449-1907
NCID
AA1197928X
Content Type
Journal Article
language
English
OAI-PMH Set
岡山大学
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© The author(s).
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isVersionOf https://www.medsci.org/v18p1831.htm
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https://creativecommons.org/licenses/by/4.0