ChatGPT in medicine: an overview of its applications, advantages, limitations, future prospects, and ethical considerations
By Tirth Dave, Sai Anirudh Athaluri, Satyam Singh. Frontiers in Artificial Intelligence, 2023
1,026 citations recorded by the source corpus.
This paper presents an analysis of the advantages, limitations, ethical considerations, future prospects, and practical applications of ChatGPT and artificial intelligence (AI) in the healthcare and medical domains. ChatGPT is an advanced language model that uses deep learning techniques to produce human-like responses to natural language inputs. It is part of the family of generative pre-training transformer (GPT) models developed by OpenAI and is currently one of the largest publicly available language models. ChatGPT is capable of capturing the nuances and intricacies of human language, allowing it to generate appropriate and contextually relevant responses across a broad spectrum of prompts. The potential applications of ChatGPT in the medical field range from identifying potential research topics to assisting professionals in clinical and laboratory diagnosis. Additionally, it can be used to help medical students, doctors, nurses, and all members of the healthcare fraternity to know about updates and new developments in their respective fields. The development of virtual assistants to aid patients in managing their health is another important application of ChatGPT in medicine. Despite its potential applications, the use of ChatGPT and other AI tools in medical writing also poses ethical and legal concerns. These include possible infringement of copyright laws, medico-legal complications, and the need for transparency in AI-generated content. In conclusion, ChatGPT has several potential applications in the medical and healthcare fields. However, these applications come with several limitations and ethical considerations which are presented in detail along with future prospects in medicine and healthcare.
Subfields: Artificial Intelligence, Health Informatics
View Paper: https://www.semanticscholar.org/paper/465b0e9fbca264713b5904c3084f8c8c6e1039b1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Artificial Intelligence
In Health Informatics
Citations in the corpus
- Generative AI in healthcare: an implementation science informed translational path on application, integration and governance (2024, background): “Generative AI aims to address various medical conditions, from chronic diseases like diabetes to acute conditions like stroke [6, 38, 60].”
- The application of large language models in medicine: A scoping review (2024, positive): “These steps will ensure that LLMs act as supplemental tools, reinforcing rather than replacing traditional learning methods 53 (Figure S1).”
- Opportunities and Challenges for ChatGPT and Large Language Models in Biomedicine and Health (2023, background): “…and challenges on ChatGPT and other LLMs for fundamental applications in seeking information and knowledge discovery in biomedicine and health, although there are several previous survey papers on general LLMs [10, 11] and use of ChatGPT for different specific health applications [12-14].”