Identification of kidney-related medications using AI from self-captured pill images-Reference-Cited by-同舟云学术

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Identification of kidney-related medications using AI from self-captured pill images

Published:2024-09-11 Issue:2 Volume:46 Page:
ISSN:0886-022X
Container-title:Renal Failure
language:en
Short-container-title:Renal Failure

Author:

Sheikh Mohammad S.¹,Dreesman Benjamin²^ORCID,Barreto Erin F.²,Thongprayoon Charat¹^ORCID,Miao Jing¹^ORCID,Suppadungsuk Supawadee¹³^ORCID,Mao Michael A.⁴^ORCID,Qureshi Fawad¹^ORCID,Pham Justin H.¹^ORCID,Craici Iasmina M.¹,Kashani Kianoush B.¹⁵^ORCID,Cheungpasitporn Wisit¹^ORCID

Affiliation:

1. Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Rochester, MN, USA

2. Department of Pharmacy, Mayo Clinic, Rochester, MN, USA

3. Chakri Naruebodindra Medical Institute, Mahidol University, Samut Prakan, Thailand

4. Division of Nephrology and Hypertension, Department of Medicine, Mayo Clinic, Jacksonville, FL, USA

5. Division of Pulmonary and Critical Care Medicine, Department of Medicine, Mayo Clinic, Rochester, MN, USA

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/0886022X.2024.2402075

Reference35 articles.

1. Prevalence and trends of polypharmacy in U.S. adults, 1999–2018

2. The rising tide of polypharmacy and drug-drug interactions: population database analysis 1995–2010

3. Trends in Prescription Drug Use Among Adults in the United States From 1999-2012

4. An update on the clinical consequences of polypharmacy in older adults: a narrative review

5. Association between polypharmacy and death: A systematic review and meta-analysis

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