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Accepted for/Published in: JMIR Diabetes

Date Submitted: Aug 27, 2024
Date Accepted: Apr 21, 2025

The final, peer-reviewed published version of this preprint can be found here:

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study

Ebrahimi N, Vakhshoori M, Teichman S, Abdipour A

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study

JMIR Diabetes 2025;10:e65846

DOI: 10.2196/65846

PMID: 40315835

PMCID: 12064210

Agreement Between Artificial Intelligence and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study

  • Niloufar Ebrahimi; 
  • Mehrbod Vakhshoori; 
  • Seigmund Teichman; 
  • Amir Abdipour

ABSTRACT

Diabetic nephropathy (DN) is one of the most frequent and severe complications of diabetes mellitus that requires early reduction for the individuals most at risk. Effective intervention and management of DN requires a patient's deep insight and helpful information. Patients require accurate information to obtain prevention advice about their kidney disease to make appropriate decisions; individuals may seek artificial intelligence (AI) as online sources instead of communicating with clinicians. Therefore, to evaluate ChatGPT and Google Bard's capabilities in providing accurate information regarding DN compared to nephrologists, we assessed their performance in answering questions related to DN. Our study revealed AI would not eliminate the need for open and detailed discussion with healthcare professionals regarding medical concerns and treatment plans, as they indicated inconsistencies in responses. Additionally, it is imperative to provide real-time health information updates to meet the needs of individuals with DN.


 Citation

Please cite as:

Ebrahimi N, Vakhshoori M, Teichman S, Abdipour A

Agreement Between AI and Nephrologists in Addressing Common Patient Questions About Diabetic Nephropathy: Cross-Sectional Study

JMIR Diabetes 2025;10:e65846

DOI: 10.2196/65846

PMID: 40315835

PMCID: 12064210

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