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Accepted for/Published in: JMIR Medical Informatics

Date Submitted: Aug 12, 2021
Date Accepted: Jan 9, 2022

The final, peer-reviewed published version of this preprint can be found here:

Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model

Sezgin E, Sirrianni J, Linwood SL

Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model

JMIR Med Inform 2022;10(2):e32875

DOI: 10.2196/32875

PMID: 35142635

PMCID: 8874824

Warning: This is an author submission that is not peer-reviewed or edited. Preprints - unless they show as "accepted" - should not be relied on to guide clinical practice or health-related behavior and should not be reported in news media as established information.

Operationalizing GPT-3 in Healthcare: An outlook of compliance, trust, and access for pretrained large AI linguistic models

  • Emre Sezgin; 
  • Joseph Sirrianni; 
  • Simon L Linwood

ABSTRACT

Generative Pre-trained Transformer (GPT) models have been popular recently with their enhanced capability and performance. In contrast to many existing Artificial Intelligence (AI) models, GPT can perform with very limited training data. GPT-3 is one of the latest releases in this pipeline, demonstrating human-like logical and intellectual responses to prompts: some examples are including writing essays, complex question answering, matching pronouns to their noun, and sentiment analysis. However, its implementation in healthcare is still a question mark in terms of operationalization and its use in clinical practice and research. In this viewpoint paper, we outlined three major operational factors that drive the adoption of GPT-3 in healthcare: (1) Health Insurance Portability and Accountability Act (HIPAA) compliance, (2) building trust with healthcare providers, and (3) establishing the broader access to the GPT-3 tools.


 Citation

Please cite as:

Sezgin E, Sirrianni J, Linwood SL

Operationalizing and Implementing Pretrained, Large Artificial Intelligence Linguistic Models in the US Health Care System: Outlook of Generative Pretrained Transformer 3 (GPT-3) as a Service Model

JMIR Med Inform 2022;10(2):e32875

DOI: 10.2196/32875

PMID: 35142635

PMCID: 8874824

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