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From ChatGPT to Treatment: the Future of AI and Large Language Models in Surgical Oncology

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Abstract

This paper explores the transformative potential of Large Language Models (LLMs) within the context of surgical oncology and outlines the foundational mechanisms behind these models. LLMs, such as GPT-4, have rapidly evolved in terms of scale and capabilities, with profound implications for their applications in healthcare. These models, rooted in the Generative Pretrained Transformer architecture, exhibit advanced natural language understanding and generation skills. Within surgical oncology, LLMs, when integrated into a Generalist Medical AI (GMAI) framework, hold great promise in offering real-time support throughout the cancer journey. However, alongside these opportunities, this paper underscores the importance of ethical, privacy, and efficacy considerations, especially in light of issues like data drift and potential biases. Collaborative efforts among healthcare providers, AI developers, and regulatory bodies are pivotal in ensuring responsible and effective use of LLMs in surgical oncology, thereby contributing to enhanced patient care and safety. As LLMs continue to advance, they are poised to become indispensable tools in the delivery of high-quality, efficient care in this specialized medical field.

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References

  1. Ramgopal S, Sanchez-Pinto LN, Horvat CM, Carroll MS, Luo Y, Florin TA (2023) Artificial intelligence-based clinical decision support in pediatrics. Pediatr Res 93(2):334–341. https://doi.org/10.1038/s41390-022-02226-1

    Article  PubMed  Google Scholar 

  2. Mascagni P, Alapatt D, Sestini L et al (2022) Computer vision in surgery: from potential to clinical value. NPJ Digit Med 5(1):163. https://doi.org/10.1038/s41746-022-00707-5

    Article  PubMed  PubMed Central  Google Scholar 

  3. Zhang Y, Jiang B, Zhang L et al (2022) Lung Nodule detectability of artificial intelligence-assisted CT image reading in lung cancer screening. Curr Med Imaging 18(3):327–334. https://doi.org/10.2174/1573405617666210806125953

    Article  PubMed  Google Scholar 

  4. Park CW, Seo SW, Kang N et al (2020) Artificial intelligence in health care: current applications and issues. J Korean Med Sci 35(42):e379. https://doi.org/10.3346/jkms.2020.35.e379

    Article  PubMed  PubMed Central  Google Scholar 

  5. Kothari AN (2023) ChatGPT, large language models, and generative AI as future augments of surgical cancer care. Ann Surg Oncol 30(6):3174–3176. https://doi.org/10.1245/s10434-023-13442-2

    Article  CAS  PubMed  Google Scholar 

  6. Thirunavukarasu AJ, Ting DSJ, Elangovan K, Gutierrez L, Tan TF, Ting DSW (2023) Large language models in medicine. Nat Med 29(8):1930–1940. https://doi.org/10.1038/s41591-023-02448-8

    Article  CAS  PubMed  Google Scholar 

  7. Temsah O, Khan SA, Chaiah Y et al (2023) Overview of early ChatGPT’s presence in medical literature: insights from a hybrid literature review by ChatGPT and human experts. Cureus. 15(4):e37281. https://doi.org/10.7759/cureus.37281

    Article  PubMed  PubMed Central  Google Scholar 

  8. Gala D, Makaryus AN (2023) The utility of language models in cardiology: a narrative review of the benefits and concerns of ChatGPT-4. Int J Environ Res Public Health 20(15):6438. https://doi.org/10.3390/ijerph20156438

    Article  PubMed  PubMed Central  Google Scholar 

  9. Egli A (2023) ChatGPT, GPT-4, and other large language models: the next revolution for clinical microbiology? Clin Infect Dis. https://doi.org/10.1093/cid/ciad407

  10. Moor M, Banerjee O, Abad ZSH et al (2023) Foundation models for generalist medical artificial intelligence. Nature. 616(7956):259–265. https://doi.org/10.1038/s41586-023-05881-4

    Article  CAS  PubMed  Google Scholar 

  11. Tiu E, Talius E, Patel P, Langlotz CP, Ng AY, Rajpurkar P (2022) Expert-level detection of pathologies from unannotated chest X-ray images via self-supervised learning. Nat Biomed Eng 6(12):1399–1406. https://doi.org/10.1038/s41551-022-00936-9

    Article  PubMed  PubMed Central  Google Scholar 

  12. Xu L, Sanders L, Li K, Chow JCL (2021) Chatbot for health care and oncology applications using artificial intelligence and machine learning: systematic review. JMIR Cancer 7(4):e27850. https://doi.org/10.2196/27850

    Article  PubMed  PubMed Central  Google Scholar 

  13. Sahiner B, Chen W, Samala RK, Petrick N (2023) Data drift in medical machine learning: implications and potential remedies. Br J Radiol 96:20220878. https://doi.org/10.1259/bjr.20220878

    Article  PubMed  Google Scholar 

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Authors and Affiliations

  1. Department of Surgical Oncology, Medical College of Wisconsin, Milwaukee, WI, USA

    Adhitya Ramamurthi & Anai N. Kothari

  2. Department of Surgery, University of Nebraska Medical Center, Omaha, NE, USA

    Chandrakanth Are

Authors
  1. Adhitya Ramamurthi
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  2. Chandrakanth Are
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  3. Anai N. Kothari
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Correspondence to Anai N. Kothari.

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Dr. Are serves as an editor for the Indian Journal of Surgical Oncology (IJSO)

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Ramamurthi, A., Are, C. & Kothari, A.N. From ChatGPT to Treatment: the Future of AI and Large Language Models in Surgical Oncology. Indian J Surg Oncol 14, 537–539 (2023). https://doi.org/10.1007/s13193-023-01836-3

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  • DOI: https://doi.org/10.1007/s13193-023-01836-3

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