Bridging artificial intelligence in medicine with generative pre-trained transformer (GPT) technology

Ethan Waisberg, Joshua Ong, Sharif Amit Kamran, Mouayad Masalkhi, Nasif Zaman, Prithul Sarker, Andrew G. Lee, Alireza Tavakkoli

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Since its public release in November 2022, the usage of ChatGPT (Open AI, USA) has been unprecedented. This large language model (LLM) can produce human-like text from deep-learning techniques. LLMs are rapidly approaching human-level performance. ChatGPT can potentially help democratize the ability to code, by allowing clinicians to be able to develop basic artificial intelligence (AI) techniques. By leveraging AI models, these clinicians can expand the scope of their research abilities, and this can potentially lead to an AI in medicine revolution, where clinicians are able to generate clinically-focused AI techniques with the goal of improving patient outcomes across all domains. In this paper, we examine the performance of ChatGPT at developing an AI program for medicine and its associated limitations and challenges. Similar to the majority of AI models, the ethical concerns surrounding its application in medicine remains, which includes biases, patient autonomy, and confidentiality, transparency, and accuracy of data. ChatGPT must also be used in accordance with local healthcare regulations, such as the Health Insurance Portability and Accountability Act (HIPAA) in the United States. All things considered, ChatGPT and future generative AI technologies will democratize the ability to code and develop AI, likely leading to breakthroughs in the medical AI sector.

Original languageEnglish (US)
Article number13
JournalJournal of Medical Artificial Intelligence
Volume6
DOIs
StatePublished - 2023

Keywords

  • Artificial intelligence (AI)
  • ChatGPT
  • large language model (LLM)
  • medicine

ASJC Scopus subject areas

  • Medicine (miscellaneous)
  • Artificial Intelligence

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