TY  - JOUR
AU  - Miao, Jing
AU  - Thongprayoon, Charat
AU  - Garcia Valencia, Oscar
AU  - Craici, Iasmina M
AU  - Cheungpasitporn, Wisit
PY  - 2024
DA  - 2024/10/10
TI  - Navigating Nephrology's Decline Through a GPT-4 Analysis of Internal Medicine Specialties in the United States: Qualitative Study
JO  - JMIR Med Educ
SP  - e57157
VL  - 10
KW  - artificial intelligence
KW  - ChatGPT
KW  - nephrology fellowship training
KW  - fellowship matching
KW  - medical education
KW  - AI
KW  - nephrology
KW  - fellowship
KW  - United States
KW  - factor
KW  - chatbots
KW  - intellectual
KW  - complexity
KW  - work-life balance
KW  - procedural involvement
KW  - opportunity
KW  - career demand
KW  - financial compensation
AB  - Background: The 2024 Nephrology fellowship match data show the declining interest in nephrology in the United States, with an 11% drop in candidates and a mere 66% (321/488) of positions filled. Objective: The study aims to discern the factors influencing this trend using ChatGPT, a leading chatbot model, for insights into the comparative appeal of nephrology versus other internal medicine specialties. Methods: Using the GPT-4 model, the study compared nephrology with 13 other internal medicine specialties, evaluating each on 7 criteria including intellectual complexity, work-life balance, procedural involvement, research opportunities, patient relationships, career demand, and financial compensation. Each criterion was assigned scores from 1 to 10, with the cumulative score determining the ranking. The approach included counteracting potential bias by instructing GPT-4 to favor other specialties over nephrology in reverse scenarios. Results: GPT-4 ranked nephrology only above sleep medicine. While nephrology scored higher than hospice and palliative medicine, it fell short in key criteria such as work-life balance, patient relationships, and career demand. When examining the percentage of filled positions in the 2024 appointment year match, nephrology’s filled rate was 66%, only higher than the 45% (155/348) filled rate of geriatric medicine. Nephrology’s score decreased by 4%‐14% in 5 criteria including intellectual challenge and complexity, procedural involvement, career opportunity and demand, research and academic opportunities, and financial compensation. Conclusions: ChatGPT does not favor nephrology over most internal medicine specialties, highlighting its diminishing appeal as a career choice. This trend raises significant concerns, especially considering the overall physician shortage, and prompts a reevaluation of factors affecting specialty choice among medical residents. 
SN  - 2369-3762
UR  - https://mededu.jmir.org/2024/1/e57157
UR  - https://doi.org/10.2196/57157
DO  - 10.2196/57157
ID  - info:doi/10.2196/57157
ER  -