Litcius/Paper detail

ChatGPT and medicine: a potential threat to science or a step towards the future?

Lucas Lacerda de Souza, Felipe Paiva Fonseca, Manoela Domingues Martins, Oslei Paes de Almeida, Hélder Antônio Rebelo Pontes, Fábio Luiz Coracin, Márcio Ajudarte Lopes, Syed Ali Khurram, Alan Roger Santos‐Silva, Ahmed M. Hagag, Pablo Agustín Vargas

2023Journal of Medical Artificial Intelligence20 citationsDOIOpen Access PDF

Abstract

Abstract: Chat generative pre-trained transformer (ChatGPT), a large language model based on the GPT-3.5 architecture, has the potential to revolutionize the field of medicine. As a machine learning tool, ChatGPT has the ability to analyze vast amounts of medical data and provide clinicians with accurate and relevant information to improve patient care. One of the key advantages of ChatGPT is its ability to assist in evidence-based medicine, as it can analyze large datasets of clinical trials and other medical studies to help identify the most effective treatments for specific conditions. ChatGPT can also aid in medical education by providing a personalized learning experience for medical students and professionals. It can assist in answering clinical questions, providing quick access to medical knowledge, and assisting in diagnosis and treatment decisions. Furthermore, ChatGPT has the potential to improve patient outcomes by reducing diagnostic errors, improving treatment plans, and enhancing patient communication. These guidelines will serve as foundational pillars for ensuring that the integration of ChatGPT into medical practices remains safe, transparent, and serves the best interests of all stakeholders involved. In conclusion, ChatGPT has the potential to transform medicine by providing clinicians with advanced tools for data analysis, assisting in diagnosis and treatment decisions, and improving patient outcomes.

Topics & Concepts

Engineering ethicsData scienceComputer scienceEngineeringArtificial Intelligence in Healthcare and EducationCOVID-19 diagnosis using AIMachine Learning in Healthcare