ArticleFrontiers in oncology2024
Evaluating ChatGPT-4o as a decision support tool in multidisciplinary sarcoma tumor boards: heterogeneous performance across various specialties.
Article in Frontiers in oncology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.
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Who cites it
14 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Applications of large language models in tumor boards: a systematic review.Oncology reviews · 2026Pooled it
- ChatGPT-4o as a decision-support tool in a urological tumour board: a prospective evaluation.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Article
- Evaluating reasoning models for therapy recommendations in gastrointestinal stromal tumors: expert and LLM-based evaluations of OpenAI o1 and DeepSeek-R1.Journal of cancer research and clinical oncology · 2026Article
- Evaluation of Artificial Intelligence as a Decision-Support Tool in Urological Tumor Boards: A Study in Real Clinical Practice.Journal of clinical medicine · 2026Article
- When AI joins the table: evaluating large language model performance in soft tissue sarcoma tumor board decisions.Journal of cancer research and clinical oncology · 2026Article
- Article
- Assessment of brachial plexus and upper-extremity peripheral nerve injuries at the anatomical level using multimodal generative models.Frontiers in surgery · 2026Article
- Exploiting artificial intelligence in precision oncology: an updated comprehensive review.Journal of translational medicine · 2025Review
- Evaluating the Concordance Between ChatGPT and Multidisciplinary Teams in Breast Cancer Treatment Planning: A Study from Bosnia and Herzegovina.Journal of clinical medicine · 2025Article
- The imitation game: large language models versus multidisciplinary tumor boards: benchmarking AI against 21 sarcoma centers from the ring trial.Journal of cancer research and clinical oncology · 2025Article
- Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline.Journal of medical Internet research · 2025Review
- The Role of Artificial Intelligence (ChatGPT-4o) in Supporting Tumor Board Decisions.Journal of clinical medicine · 2025Article
- A comparative study on DeepSeek and ChatGPT for bone and soft tissue tumor clinical practice.Frontiers in oncology · 2025Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background and objectives: Since the launch of ChatGPT in 2023, large language models have attracted substantial interest to be deployed in the health care sector. This study evaluates the performance of ChatGPT-4o as a support tool for decision-making in multidisciplinary sarcoma tumor boards. Methods: We created five sarcoma patient cases mimicking real-world scenarios and prompted ChatGPT-4o to issue tumor board decisions. These recommendations were independently assessed by a multidisciplinary panel, consisting of an orthopedic surgeon, plastic surgeon, radiation oncologist, radiologist, and pathologist. Assessments were graded on a Likert scale from 1 (completely disagree) to 5 (completely agree) across five categories: understanding, therapy/diagnostic recommendation, aftercare recommendation, summarization, and support tool effectiveness. Results: The mean score for ChatGPT-4o performance was 3.76, indicating moderate effectiveness. Surgical specialties received the highest score, with a mean score of 4.48, while diagnostic specialties (radiology/pathology) performed considerably better than the radiation oncology specialty, which performed poorly. Conclusions: This study provides initial insights into the use of prompt-engineered large language models as decision support tools in sarcoma tumor boards. ChatGPT-4o recommendations regarding surgical specialties performed best while ChatGPT-4o struggled to give valuable advice in the other tested specialties. Clinicians should understand both the advantages and limitations of this technology for effective integration into clinical practice.
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