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

被引:8
|
作者
Ramamurthi, Adhitya [1 ]
Are, Chandrakanth [2 ]
Kothari, Anai N. [1 ]
机构
[1] Med Coll Wisconsin, Dept Surg Oncol, Milwaukee, WI 53226 USA
[2] Univ Nebraska Med Ctr, Dept Surg, Omaha, NE USA
关键词
LLMs; Surgical oncology; AI;
D O I
10.1007/s13193-023-01836-3
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
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.
引用
收藏
页码:537 / 539
页数:3
相关论文
共 50 条
  • [21] ChatGPT and large language models in orthopedics: from education and surgery to research
    Srijan Chatterjee
    Manojit Bhattacharya
    Soumen Pal
    Sang-Soo Lee
    Chiranjib Chakraborty
    Journal of Experimental Orthopaedics, 10
  • [22] Large language model artificial intelligence: the current state and future of ChatGPT in neuro-oncology publishing
    Cifarelli, Christopher P.
    Sheehan, Jason P.
    JOURNAL OF NEURO-ONCOLOGY, 2023, 163 (02) : 473 - 474
  • [23] Large language model artificial intelligence: the current state and future of ChatGPT in neuro-oncology publishing
    Christopher P. Cifarelli
    Jason P. Sheehan
    Journal of Neuro-Oncology, 2023, 163 : 473 - 474
  • [24] Academic Integrity considerations of AI Large Language Models in the post-pandemic era: ChatGPT and beyond
    Perkins, Mike
    JOURNAL OF UNIVERSITY TEACHING AND LEARNING PRACTICE, 2023, 20 (02):
  • [25] ChatGPT and the rise of large language models: the new AI-driven infodemic threat in public health
    De Angelis, Luigi
    Baglivo, Francesco
    Arzilli, Guglielmo
    Privitera, Gaetano Pierpaolo
    Ferragina, Paolo
    Tozzi, Alberto Eugenio
    Rizzo, Caterina
    FRONTIERS IN PUBLIC HEALTH, 2023, 11
  • [26] Generative AI and simulation modeling: how should you (not) use large language models like ChatGPT
    Akhavan, Ali
    Jalali, Mohammad
    SYSTEM DYNAMICS REVIEW, 2024, 40 (03)
  • [27] Comment on: Artificial intelligence and large language models-including ChatGPT-in pediatric hematology/oncology
    Daungsupawong, Hinpetch
    Wiwanitkit, Viroj
    PEDIATRIC BLOOD & CANCER, 2024,
  • [28] Future applications of generative large language models: A data-driven case study on ChatGPT
    Chiarello, Filippo
    Giordano, Vito
    Spada, Irene
    Barandoni, Simone
    Fantoni, Gualtiero
    TECHNOVATION, 2024, 133
  • [29] ChatGPT and large language models in academia: opportunities and challenges
    Jesse G. Meyer
    Ryan J. Urbanowicz
    Patrick C. N. Martin
    Karen O’Connor
    Ruowang Li
    Pei-Chen Peng
    Tiffani J. Bright
    Nicholas Tatonetti
    Kyoung Jae Won
    Graciela Gonzalez-Hernandez
    Jason H. Moore
    BioData Mining, 16
  • [30] ChatGPT and large language models in academia: opportunities and challenges
    Meyer, Jesse G.
    Urbanowicz, Ryan J.
    Martin, Patrick C. N.
    O'Connor, Karen
    Li, Ruowang
    Peng, Pei-Chen
    Bright, Tiffani J.
    Tatonetti, Nicholas
    Won, Kyoung Jae
    Gonzalez-Hernandez, Graciela
    Moore, Jason H.
    BIODATA MINING, 2023, 16 (01)