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

This research letter presents a cross-sectional analysis comparing the agreement between artificial intelligence models and nephrologists in responding to common patient questions about diabetic nephropathy.

Authors

Institutions

Publication Details

Journal
JMIR Diabetes
Published
2025-04-21
DOI
https://doi.org/10.2196/65846
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Niloufar Ebrahimi, Sam L. Teichman, Mehrbod Vakhshoori, Amir Abdipour
JMIR Diabetes
Artificial Intelligence in Healthcare and Education
article

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

Niloufar Ebrahimi, Sam L. Teichman, Mehrbod Vakhshoori, Amir Abdipour
article en

Abstract

This research letter presents a cross-sectional analysis comparing the agreement between artificial intelligence models and nephrologists in responding to common patient questions about diabetic nephropathy.

JMIR DiabetesVol. 10
Loma Linda University Medical Center (US), Loma Linda University (US)
Openalex Percentile: Top 95%
Artificial Intelligence in Healthcare and Education
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.