AI chatbots not yet ready for clinical use. Joshua Au Yeung, Krajevic, Z., Balston, A., Idowu, E., Dobson, R., & Teo, J. T MedRxiv, March, 2023. Place: Cold Spring Harbor Publisher: Cold Spring Harbor Laboratory Press
AI chatbots not yet ready for clinical use [link]Paper  doi  abstract   bibtex   
As large language models (LLMs) expand and become more advanced, so does the natural language processing capabilities of conversational AI, or "chatbots". OpenAIs recent release, ChatGPT, uses transformer-based model and deep learning algorithms to enable human-like text generation and question-answering on general domain knowledge, while a healthcare-specific Large Language Model (LLM), Gatortron has focused on the real-world healthcare domain knowledge. As LLMs advance to achieve near human-level performances on medical question and answering benchmarks, it is probable that Conversational AI will soon be developed for use in healthcare. In this article we briefly compare the performance of two different approaches to generative LLMs - ChatGPT and Foresight NLP model, in forecasting relevant diagnoses based on clinical vignettes. We also discuss important considerations and limitations of transformer-based chatbots for clinical use.
@article{joshua_au_yeung_ai_2023,
	title = {{AI} chatbots not yet ready for clinical use},
	url = {https://www.proquest.com/working-papers/ai-chatbots-not-yet-ready-clinical-use/docview/2782843334/se-2},
	doi = {10.1101/2023.03.02.23286705},
	abstract = {As large language models (LLMs) expand and become more advanced, so does the natural language processing capabilities of conversational AI, or "chatbots". OpenAIs recent release, ChatGPT, uses transformer-based model and deep learning algorithms to enable human-like text generation and question-answering on general domain knowledge, while a healthcare-specific Large Language Model (LLM), Gatortron has focused on the real-world healthcare domain knowledge. As LLMs advance to achieve near human-level performances on medical question and answering benchmarks, it is probable that Conversational AI will soon be developed for use in healthcare. In this article we briefly compare the performance of two different approaches to generative LLMs - ChatGPT and Foresight NLP model, in forecasting relevant diagnoses based on clinical vignettes. We also discuss important considerations and limitations of transformer-based chatbots for clinical use.},
	language = {English},
	journal = {MedRxiv},
	author = {{Joshua Au Yeung} and Krajevic, Zeljko and Balston, Alfred and Idowu, Esther and Dobson, Richard and Teo, James T},
	month = mar,
	year = {2023},
	note = {Place: Cold Spring Harbor
Publisher: Cold Spring Harbor Laboratory Press},
	keywords = {Language, Health care, Medical Sciences, Deep learning},
}

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