Concordance Between a Generative Artificial Intelligence Model and a Hepatobiliary Multidisciplinary Team in Hepatocellular Carcinoma Management: A Retrospective Study.
Sep 2026· Annals of Surgical Oncology· 0 citations· 15 references
Medicine
TL;DR
In HCC management, AI demonstrated a high level of agreement with expert MDT decisions, suggesting its potential role as a complementary decision-support tool, however, limitations persist for elderly patients and borderline clinical scenarios, in which individualized human judgment remains essential.
LLM-generated treatment recommendations demonstrated moderate alignment with MDT decisions in HPB oncology, indicating that concordance alone is insufficient for evaluating LLMs as clinical decision support tools.
Jun-Jo Sung, Eui Hyuk Chong, Incheon Kang et al.· Journal of Medical Internet...· 0 citations
Current evidence is insufficient to establish improvements in MDT decision quality or patient outcomes, and AI should be regarded as a supervised support tool rather than a replacement for expert multidisciplinary judgment.
A. Nikitaras, S. M. Tsoti, M. Pramateftakis· Frontiers in Oncology· 0 citations
Background/Objectives: Breast cancer management relies on multidisciplinary team (MDT) decisions that integrate clinical, radiological, pathological, and patient-related factors. Large language models (LLMs) may support such decisions, but evidence based on real-world cases remains limited. Methods: We evaluated the ag...
G. Dindelegan, Noé Yoshi François Poupel, George Ionuț Golea et al.· Journal of Clinical Medicine· 0 citations
Background Hepatocellular carcinoma (HCC) treatment selection demands nuanced integration of heterogeneous patient data, yet prevailing predictive models rely on restricted data modalities and oversimplified therapeutic frameworks, compromising clinical translation. Objective We developed and validated a multimodal art...
W. Feng, S. Liu, Z. Yang et al.· medRxiv· 0 citations
Colorectal multidisciplinary teams (MDTs) face increasing workload. We evaluated whether routinely collected colorectal MDT variables could support local MDT concordance modelling, interpretable feature attribution, and provider-side budget impact estimation.
Prospective observational cohort of 250 consecu...
Mohammed Hamid, Muhammad Mushtaq, Farhan Javed et al.· International Journal of Col...· 0 citations
Introduction Multidisciplinary tumour board (MTB) or tumour board (TB) is the “gold standard” for providing oncological patients’ diagnosis and treatment. Often, MTBs are time-intensive, capacity-constrained, and absent or inconsistent in many routine hospitals. Despite that, in MTB, a few experienced specialists in th...
O. Ivashchuk, S. Hovornyan· Frontiers in Oncology· 0 citations
We use cookies to run the site and, with your consent, for analytics and to show ads.
See our Cookie Policy.