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Large language models (LLMs) are becoming increasingly relevant as a potential tool for healthcare, aiding communication between clinicians, researchers, and patients.
Language models are few-shot learners
Brown, T., Mann, B., Ryder, N., Subbiah, M., Kaplan, J. D., Dhariwal, P., Neelakantan, A., Shyam, P., Sastry, G., Askell, A., et al. (2020) · 1901
Earlier work this paper cites.
Cyberchondria: studies of the escalation of medical concerns in web search
White, R. W. and Horvitz, E. (2009) · 2009
Earlier work this paper cites.
Flaws in clinical reasoning: a common cause of diagnostic error
Wellbery, C. (2011) · 2011
Earlier work this paper cites.
Health workforce requirements for universal health coverage and the sustainable development goals.(human resources for health observer, 17)
Organization, W. H. et al. (2016) · 2016
Earlier work this paper cites.
Deep reinforcement learning from human preferences
Christiano, P. F., Leike, J., Brown, T., Martic, M., Legg, S., and Amodei, D. (2017) · 2017
Earlier work this paper cites.
A mixed methods systematic review of the effects of patient online self-diagnosing in the ‘smart-phone society’on the healthcare professional-patient relationship and medical authority
Farnood, A., Johnston, B., and Mair, F. S. (2020) · 2020
Earlier work this paper cites.
What disease does this patient have? a large-scale open domain question answering dataset from medical exams
Jin, D., Pan, E., Oufattole, N., Weng, W.-H., Fang, H., and Szolovits, P. (2021) · 2021
Cited alongside, same era.
Pathways: Asynchronous distributed dataflow for ml
Barham, P., Chowdhery, A., Dean, J., Ghemawat, S., Hand, S., Hurt, D., Isard, M., Lim, H., Pang, R., Roy, S., et al. (2022) · 2022
Cited alongside, same era.
Can large language models reason about medical questions?
Liévin, V., Hother, C. E., and Winther, O. (2022) · 2022
Cited alongside, same era.
Lamda: Language models for dialog applications
Thoppilan, R., De Freitas, D., Hall, J., Shazeer, N., Kulshreshtha, A., Cheng, H.-T., Jin, A., Bos, T., Baker, L., Du, Y., et al. (2022) · 2022
Cited alongside, same era.
Self-diagnosis and large language models: A new front for medical misinformation
The imperative for regulatory oversight of large language models (or generative ai) in healthcare
Meskó, B. and Topol, E. J. (2023) · 2023
Closest in time.
Gpt-4 technical report
OpenAI, R. (2023) · 2023
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Towards expert-level medical question answering with large language models
Singhal, K., Tu, T., Gottweis, J., Sayres, R., Wulczyn, E., Hou, L., Clark, K., Pfohl, S., Cole-Lewis, H., Neal, D., et al. (2023) · 2023
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Large language models in medicine
Thirunavukarasu, A. J., Ting, D. S. J., Elangovan, K., Gutierrez, L., Tan, T. F., and Ting, D. S. W. (2023) · 2023
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Llama 2: Open foundation and fine-tuned chat models
Touvron, H., Martin, L., Stone, K., Albert, P., Almahairi, A., Babaei, Y., Bashlykov, N., Batra, S., Bhargava, P., Bhosale, S., et al. (2023) · 2023
Closest in time.
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Barnard, F., Van Sittert, M., and Rambhatla, S. (2023) · 2023
Cited alongside, same era.
Attention is not all you need: the complicated case of ethically using large language models in healthcare and medicine
Harrer, S. (2023) · 2023
Cited alongside, same era.