Background: Artificial intelligence (AI) has the potential to revolutionize the way medicine is learned, taught, and practiced, and medical education must prepare learners for these inevitable changes. Academic medicine has, however, been slow to embrace recent AI advances. Since its launch in November 2022, ChatGPT has emerged as a fast and user-friendly large language model that can assist health care professionals, medical educators, students, trainees, and patients. While many studies focus on the technology's capabilities, potential, and risks, there is a gap in studying the perspective of end users.

Objective: The aim of this study was to gauge the experiences and perspectives of graduating medical students on ChatGPT and AI in their training and future careers.

Methods: A cross-sectional web-based survey of recently graduated medical students was conducted in an international academic medical center between May 5, 2023, and June 13, 2023. Descriptive statistics were used to tabulate variable frequencies.

Results: Of 325 applicants to the residency programs, 265 completed the survey (an 81.5% response rate). The vast majority of respondents denied using ChatGPT in medical school, with 20.4% (n=54) using it to help complete written assessments and only 9.4% using the technology in their clinical work (n=25). More students planned to use it during residency, primarily for exploring new medical topics and research (n=168, 63.4%) and exam preparation (n=151, 57%). Male students were significantly more likely to believe that AI will improve diagnostic accuracy (n=47, 51.7% vs n=69, 39.7%; P=.001), reduce medical error (n=53, 58.2% vs n=71, 40.8%; P=.002), and improve patient care (n=60, 65.9% vs n=95, 54.6%; P=.007). Previous experience with AI was significantly associated with positive AI perception in terms of improving patient care, decreasing medical errors and misdiagnoses, and increasing the accuracy of diagnoses (P=.001, P<.001, P=.008, respectively).

Conclusions: The surveyed medical students had minimal formal and informal experience with AI tools and limited perceptions of the potential uses of AI in health care but had overall positive views of ChatGPT and AI and were optimistic about the future of AI in medical education and health care. Structured curricula and formal policies and guidelines are needed to adequately prepare medical learners for the forthcoming integration of AI in medicine.

Download full-text PDF

Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10770787PMC
http://dx.doi.org/10.2196/51302DOI Listing

Publication Analysis

Top Keywords

medical
10
artificial intelligence
8
medical students
8
patient care
8
students
5
medical student
4
student experiences
4
experiences perceptions
4
chatgpt
4
perceptions chatgpt
4

Similar Publications

In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Transformers (BERT) to identify privacy information and to verify the feasibility of our method for privacy protection in the Chinese clinical context. We collected and double-annotated 33,017 discharge summaries from 151 medical institutions on a municipal regional health information platform, developed a BERT-based Bidirectional Long Short-Term Memory Model (BiLSTM) and Conditional Random Field (CRF) model, and tested the performance of privacy identification on the dataset. To explore the performance of different substructures of the neural network, we created five additional baseline models and evaluated the impact of different models on performance.

View Article and Find Full Text PDF

Background: To compare plateletcount (PC), mean platelet volume (MPV), and platelet distribution width (PDW)between women with preeclampsia (PE) and normotensive pregnant women, andevaluate their effectiveness as predictors of PE.

Research Design Andmethods: This cross-sectionalstudy at Nishtar Hospital, Multan, included 141 women: 74 normotensive and 67preeclamptic. Data was collected using an automated hematology analyzer andanalyzed with SPSS version 26 and ROC curves.

View Article and Find Full Text PDF

The 18 Workshop on Recent Issues in Bioanalysis (18 WRIB) took place in San Antonio, TX, USA on May 6-10, 2024. Over 1100 professionals representing pharma/biotech companies, CROs, and multiple regulatory agencies convened to actively discuss the most current topics of interest in bioanalysis. The 18 WRIB included 3 Main Workshops and 7 Specialized Workshops that together spanned 1 week to allow an exhaustive and thorough coverage of all major issues in bioanalysis of biomarkers, immunogenicity, gene therapy, cell therapy and vaccines.

View Article and Find Full Text PDF

This study investigates the effectiveness of blood flow restriction (BFR) training in maintaining athletic performance during a taper phase in basketball players. The taper phase aims to reduce external load while maintaining training intensity. Seventeen experienced basketball players were randomised into two groups: a placebo group ( = 8, 22.

View Article and Find Full Text PDF

Cellular Cholesterol Loss Impairs Synaptic Vesicle Mobility via the CAMK2/Synapsin-1 Signaling Pathway.

Front Biosci (Landmark Ed)

January 2025

Department of Neurology, Jinshan Hospital, Fudan University, 201508 Shanghai, China.

Background: Neuronal cholesterol deficiency may contribute to the synaptopathy observed in Alzheimer's disease (AD). However, the underlying mechanisms remain poorly understood. Intact synaptic vesicle (SV) mobility is crucial for normal synaptic function, whereas disrupted SV mobility can trigger the synaptopathy associated with AD.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!