ChatGPT and the Future of Health Policy Analysis: Potential and Pitfalls of Using ChatGPT in Policymaking

Developing a hetero-intelligence methodological framework for sustainable policy-making based on the assessment of large language models

This work delves into the increasing relevance of Large Language Models (LLMs) in the realm of sustainable policy-making, proposing an innovative hetero-intelligence framework that blends human and artificial intelligence (AI) for tackling modern sustainability challenges. The research methodology includes a hetero-intelligence performance test, which juxtaposes human intelligence with AI in the formulation and implementation of sustainable policies. After testing this hetero-intelligence methodology, seven steps are rigorously described so that it can be replicated in any sustainability planning related context. The results underscore the capabilities and limitations of LLMs, underscoring the critical role of human intelligence in enhancing the efficacy of hetero-intelligence systems. This work fulfils the need of a rigorous methodological framework based on empirical steps that can provide unbiased outcomes to be integrated into sustainable planning and decision-making processes.•Assesses LLMs' limitations and capabilities regarding sustainable planning issues•A replicable methodology is proposed based on the combination of both human and artificial intelligence•It proposes and systematises the integration of a hetero-intelligent approach into the formulation of sustainability policies to be more efficient and effective.

Harnessing ChatGPT and GPT-4 for evaluating the rheumatology questions of the Spanish access exam to specialized medical training

The emergence of large language models (LLM) with remarkable performance such as ChatGPT and GPT-4, has led to an unprecedented uptake in the population. One of their most promising and studied applications concerns education due to their ability to understand and generate human-like text, creating a multitude of opportunities for enhancing educational practices and outcomes. The objective of this study is twofold: to assess the accuracy of ChatGPT/GPT-4 in answering rheumatology questions from the access exam to specialized medical training in Spain (MIR), and to evaluate the medical reasoning followed by these LLM to answer those questions. A dataset, RheumaMIR, of 145 rheumatology-related questions, extracted from the exams held between 2010 and 2023, was created for that purpose, used as a prompt for the LLM, and was publicly distributed. Six rheumatologists with clinical and teaching experience evaluated the clinical reasoning of the chatbots using a 5-point Likert scale and their degree of agreement was analyzed. The association between variables that could influence the models' accuracy (i.e., year of the exam question, disease addressed, type of question and genre) was studied. ChatGPT demonstrated a high level of performance in both accuracy, 66.43%, and clinical reasoning, median (Q1-Q3), 4.5 (2.33-4.67). However, GPT-4 showed better performance with an accuracy score of 93.71% and a median clinical reasoning value of 4.67 (4.5-4.83). These findings suggest that LLM may serve as valuable tools in rheumatology education, aiding in exam preparation and supplementing traditional teaching methods.

The Double-Edged Sword of AI in Biomedical Engineering: ChatGPT's Controversial Impact on Research and Collaboration Paradigms

As artificial intelligence (AI) permeates various fields, ChatGPT emerges as a contentious force in biomedical engineering, stirring both excitement and concern. This letter explores the disruptive potential and controversial implications of ChatGPT on research, collaboration, and the future of the field. By presenting thought-provoking questions and confronting divisive issues, we aim to spark a lively debate on the responsible integration of AI technology in biomedical engineering while safeguarding the essence of human expertise.

Artificial Intelligence in Sports Medicine: Could GPT-4 Make Human Doctors Obsolete?

Sports medicine, an essential branch of orthopedics, focuses on preserving, restoring, improving, and rebuilding the function of the human motor system. As a thriving interdisciplinary field, sports medicine attracts not only the interest of the orthopedic community, but also artificial intelligence (AI). In this study, our team summarized the potential applications of GPT-4 in sports medicine including diagnostic imaging, exercise prescription, medical supervision, surgery treatment, sports nutrition, and science research. In our opinion, it is impossible that GPT-4 could make sports physicians obsolete. Instead, it could become an indispensable scientific assistant for sport doctors in future.