An Adapted Neural-Fuzzy Inference System Model Using Preprocessed Balance Data to Improve the Predictive Accuracy of Warfarin Maintenance Dosing in Patients After Heart Valve Replacement-Reference-Cited by-同舟云学术

An Adapted Neural-Fuzzy Inference System Model Using Preprocessed Balance Data to Improve the Predictive Accuracy of Warfarin Maintenance Dosing in Patients After Heart Valve Replacement

Published:2021-04-20 Issue: Volume: Page:
ISSN:0920-3206
Container-title:Cardiovascular Drugs and Therapy
language:en
Short-container-title:Cardiovasc Drugs Ther

Author:

Gu Zhi-Chun^ORCID,Huang Shou-Rui,Dong Li,Zhou Qin,Wang Jing,Fu Bo,Chen Jin

Funder

National Natural Science Foundation of China

Research Funds of Shanghai Health and Family Planning commission

Cultivation fund of clinical research of Renji Hospital

Clinical Pharmacy Innovation Research Institute of Shanghai Jiao Tong University School of Medicine

Shanghai “Rising Stars of Medical Talent” Youth Development Program – Youth Medical Talents – Clinical Pharmacist Program

Publisher

Springer Science and Business Media LLC

Subject

Pharmacology (medical),Cardiology and Cardiovascular Medicine,Pharmacology,General Medicine

Link

https://link.springer.com/content/pdf/10.1007/s10557-021-07191-1.pdf

Reference37 articles.

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3. Sconce EA, Khan TI, Wynne HA, Avery P, Monkhouse L, King BP, et al. The impact of CYP2C9 and VKORC1 genetic polymorphism and patient characteristics upon warfarin dose requirements: proposal for a new dosing regimen. Blood. 2005;106(7):2329–33.

4. Jorgensen AL, Pirmohamed M. Risk modeling strategies for pharmacogenetic studies. Pharmacogenomics. 2011;12(3):397–410.

5. Yan H, Yin J-Y, Zhang W, Li X. Possible strategies to make warfarin dosing algorithm prediction more accurately in patients with extreme dose. Clin Pharmacol Therap. 2018;103(2):184.

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