Skip to main content
SpringerLink
Log in

Will generalist medical artificial intelligence be the future path for health-related natural language processing models?

  • Correspondence
  • Published:
Prostate Cancer and Prostatic Diseases Submit manuscript

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

References

  1. Cocci A, Pezzoli M, Lo Re M, Russo GI, Asmundo MG, Fode M, et al. Quality of information and appropriateness of ChatGPT outputs for urology patients. Prostate Cancer Prostatic Dis. 2023;101038. https://doi.org/10.1038/s41391-023-00705-y.

  2. Davis R, Eppler M, Ayo-Ajibola O, Loh-Doyle JC, Nabhani J, Samplaski M, et al. Evaluating the effectiveness of artificial intelligence-powered large language models application in disseminating appropriate and readable health information in urology. J Urol. 2023;101097. https://doi.org/10.1097/JU.0000000000003656.

  3. Xv Y, Peng C, Wei Z, Liao F, Xiao M. Can Chat-GPT a substitute for urological resident physician in diagnosing diseases? A preliminary conclusion from an exploratory investigation. World J Urol. 2023;41:2569–71.

    Article  PubMed  Google Scholar 

  4. Deebel NA, Terlecki R. ChatGPT performance on the American Urological Association self-assessment study program and the potential influence of artificial intelligence in urologic training. Urology. 2023;177:29–33.

    Article  PubMed  Google Scholar 

  5. Moor M, Banerjee O, Abad ZSH, Krumholz HM, Leskovec J, Topol EJ, et al. Foundation models for generalist medical artificial intelligence. Nature. 2023;616:259–65.

    Article  CAS  PubMed  Google Scholar 

Download references

Acknowledgements

This article was a result of a collaborative effort involving multiple institutions. The authors would like to extend their gratitude to Prof. Y.Q. Wang from Hebei University (HBU) for providing insightful explanations about the generalist medical artificial intelligence (GMAI).

Author information

Authors and Affiliations

  1. Department of Pediatrics, Xuzhou Medical University, Xuzhou, 221004, China

    Huajie Di & Yi Wen

  2. Evidence-Based Medicine Research Center, Xuzhou Medical University, Xuzhou, 221004, China

    Huajie Di

  3. Department of Pediatric Urology, The Affiliated Xuzhou Children’s Hospital of Xuzhou Medical University, Xuzhou, 221002, China

    Huajie Di & Yi Wen

Authors
  1. Huajie Di
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Yi Wen
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

Conceptualization: HJD, YW; Writing—Original Draft: HJD; Writing—Review & Editing: HJD, YW.

Corresponding author

Correspondence to Yi Wen.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Di, H., Wen, Y. Will generalist medical artificial intelligence be the future path for health-related natural language processing models?. Prostate Cancer Prostatic Dis (2023). https://doi.org/10.1038/s41391-023-00719-6

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1038/s41391-023-00719-6

  • Springer Nature Limited

This article is cited by

Search

Navigation