TY - JOUR
T1 - Bridging artificial intelligence in medicine with generative pre-trained transformer (GPT) technology
AU - Waisberg, Ethan
AU - Ong, Joshua
AU - Kamran, Sharif Amit
AU - Masalkhi, Mouayad
AU - Zaman, Nasif
AU - Sarker, Prithul
AU - Lee, Andrew G.
AU - Tavakkoli, Alireza
N1 - Funding Information:
This study was supported by NASA Grant (No. 80NSSC20K183): A Non-intrusive Ocular Monitoring Framework to Model Ocular Structure and Functional Changes due to Long-term Spaceflight.
Funding Information:
Funding: This study was supported by NASA Grant (No.
Publisher Copyright:
© Journal of Medical Artificial Intelligence. All rights reserved.
PY - 2023
Y1 - 2023
N2 - 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.
AB - 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.
KW - Artificial intelligence (AI)
KW - ChatGPT
KW - large language model (LLM)
KW - medicine
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U2 - 10.21037/jmai-23-36
DO - 10.21037/jmai-23-36
M3 - Article
AN - SCOPUS:85172797304
SN - 2617-2496
VL - 6
JO - Journal of Medical Artificial Intelligence
JF - Journal of Medical Artificial Intelligence
M1 - 13
ER -