%0 Journal Article
%@ 2369-3762
%I JMIR Publications
%V 10
%N 
%P e57157
%T Navigating Nephrology's Decline Through a GPT-4 Analysis of Internal Medicine Specialties in the United States: Qualitative Study
%A Miao,Jing
%A Thongprayoon,Charat
%A Garcia Valencia,Oscar
%A Craici,Iasmina M
%A Cheungpasitporn,Wisit
%K artificial intelligence
%K ChatGPT
%K nephrology fellowship training
%K fellowship matching
%K medical education
%K AI
%K nephrology
%K fellowship
%K United States
%K factor
%K chatbots
%K intellectual
%K complexity
%K work-life balance
%K procedural involvement
%K opportunity
%K career demand
%K financial compensation
%D 2024
%7 10.10.2024
%9 
%J JMIR Med Educ
%G English
%X 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. 
%R 10.2196/57157
%U https://mededu.jmir.org/2024/1/e57157
%U https://doi.org/10.2196/57157