Published on in Vol 10, No 2 (2022): February

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/32875, first published .
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

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

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

Authors of this article:

Emre Sezgin1 Author Orcid Image ;   Joseph Sirrianni1 Author Orcid Image ;   Simon L Linwood2 Author Orcid Image

Journals

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  3. Lee J, Yang S, Holland-Hall C, Sezgin E, Gill M, Linwood S, Huang Y, Hoffman J. Prevalence of Sensitive Terms in Clinical Notes Using Natural Language Processing Techniques: Observational Study. JMIR Medical Informatics 2022;10(6):e38482 View
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  6. Sirrianni J, Sezgin E, Claman D, Linwood S. Medical Text Prediction and Suggestion Using Generative Pretrained Transformer Models with Dental Medical Notes. Methods of Information in Medicine 2022;61(05/06):195 View
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  29. Fear K, Gleber C. Shaping the Future of Older Adult Care: ChatGPT, Advanced AI, and the Transformation of Clinical Practice. JMIR Aging 2023;6:e51776 View
  30. Pagano S, Holzapfel S, Kappenschneider T, Meyer M, Maderbacher G, Grifka J, Holzapfel D. Arthrosis diagnosis and treatment recommendations in clinical practice: an exploratory investigation with the generative AI model GPT-4. Journal of Orthopaedics and Traumatology 2023;24(1) View
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  33. Chen A, Chen D, Tian L. Benchmarking the symptom-checking capabilities of ChatGPT for a broad range of diseases. Journal of the American Medical Informatics Association 2024;31(9):2084 View
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  41. Alqudah M. The Use of Generative Artificial Intelligence for Customer Services. SSRN Electronic Journal 2024 View
  42. Spotnitz M, Idnay B, Gordon E, Shyu R, Zhang G, Liu C, Cimino J, Weng C. A Survey of Clinicians' Views of the Utility of Large Language Models. Applied Clinical Informatics 2024;15(02):306 View
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  44. Safdar M, Siddique N, Gulzar A, Adil S, Yasin H, Khan M. A bibliometric analysis of literature published on ChatGPT and GPT. Global Knowledge, Memory and Communication 2024 View
  45. Sezgin E, McKay I. Behavioral health and generative AI: a perspective on future of therapies and patient care. npj Mental Health Research 2024;3(1) View
  46. Claman D, Sezgin E. Artificial Intelligence in Dental Education: Opportunities and Challenges of Large Language Models and Multimodal Foundation Models. JMIR Medical Education 2024;10:e52346 View
  47. Xu J, Lu L, Peng X, Pang J, Ding J, Yang L, Song H, Li K, Sun X, Zhang S. Data Set and Benchmark (MedGPTEval) to Evaluate Responses From Large Language Models in Medicine: Evaluation Development and Validation. JMIR Medical Informatics 2024;12:e57674 View
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  52. Marchena Sekli G. The research landscape on generative artificial intelligence: a bibliometric analysis of transformer-based models. Kybernetes 2024 View
  53. Sezgin E, Sirrianni J, Kranz K. Evaluation of a Digital Scribe: Conversation Summarization for Emergency Department Consultation Calls. Applied Clinical Informatics 2024;15(03):600 View
  54. Kim P, Seo B, De Silva H. Concordance of clinician, Chat-GPT4, and ORAD diagnoses against histopathology in Odontogenic Keratocysts and tumours: a 15-Year New Zealand retrospective study. Oral and Maxillofacial Surgery 2024;28(4):1557 View
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Books/Policy Documents

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