ReviewIndian journal of surgical oncology2023
From ChatGPT to Treatment: the Future of AI and Large Language Models in Surgical Oncology.
Review in Indian journal of surgical oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 18 citations in OpenAlex.
- Applying transformer-based deep learning models in image-driven cancer diagnosis: a comprehensive bibliometric analysis of global research trends.Frontiers in oncology · 2026Pooled it
- ChatGPT in liver transplantation: Current applications, limitations, and future directions.World journal of transplantation · 2026Review
- Temporal evolution of large language models (LLMs) in oncology.Journal of translational medicine · 2025Article
- Article
- Large Language Models in Gastroenterology and Gastrointestinal Surgery: A New Frontier in Patient Communication and Education.Gastroenterology research · 2025Review
- From the Desk of Editors: Surgical Oncology-Embracing Change and Enduring Relevance.Indian journal of surgical oncology · 2025Article
- Large language models in cancer: potentials, risks, and safeguards.BJR artificial intelligence · 2025Review
- From the desk of editors: Crafting Manuscripts for IJSO.Indian journal of surgical oncology · 2024Article
- Accuracy and consistency of publicly available Large Language Models as clinical decision support tools for the management of colon cancer.Journal of surgical oncology · 2024Article
- AI-Generated Content in Cancer Symptom Management: A Comparative Analysis Between ChatGPT and NCCN.Journal of pain and symptom management · 2024Article
- Assessment of the information provided by ChatGPT regarding exercise for patients with type 2 diabetes: a pilot study.BMJ health & care informatics · 2024Article
- AI and Ethics: A Systematic Review of the Ethical Considerations of Large Language Model Use in Surgery Research.Healthcare (Basel, Switzerland) · 2024Review
- Comment on "From ChatGPT to Treatment: the Future of AI and Large Language Models in Surgical Oncology".Indian journal of surgical oncology · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.