Application of Artificial Intelligence in Multidisciplinary Decision-Making for Head and Neck Cancer

Given the complex nature of head and neck cancers, multidisciplinary team (MDT) management has become increasingly important in contemporary oncologic care. However, MDT implementation often faces practical limitations due to time constraints, limited resources, and coordination challenges among specialists. To address these issues, there is a growing need for innovative decision-support tools. Recent advances in artificial intelligence (AI), particularly large language models (LLMs), have introduced new opportunities to enhance clinical decision-making. This review explores the current applications of AI technologies in oncologic treatment decision processes, with a focus on their potential integration into MDT-based decision-making for head and neck cancer. Furthermore, we introduce recent studies applying multi-agent LLM frameworks to MDT systems and discuss key challenges that must be addressed for successful clinical adoption. Ultimately, this review envisions an AI-augmented MDT model that enhances decision-making efficiency and objectivity, while enabling clinicians to focus more deeply on their core role—delivering optimal patient-centered cancer care.

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Publication Details

Journal
Korean Society for Head and Neck Oncology
Published
2025-11-30
DOI
https://doi.org/10.21593/kjhno/2025.41.2.1
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Application of Artificial Intelligence in Multidisciplinary Decision-Making for Head and Neck Cancer

Young Chan Lee
Korean Society for Head and Neck Oncology
Artificial Intelligence in Healthcare and Education
article

Application of Artificial Intelligence in Multidisciplinary Decision-Making for Head and Neck Cancer

Young Chan Lee
article en

Abstract

Given the complex nature of head and neck cancers, multidisciplinary team (MDT) management has become increasingly important in contemporary oncologic care. However, MDT implementation often faces practical limitations due to time constraints, limited resources, and coordination challenges among specialists. To address these issues, there is a growing need for innovative decision-support tools. Recent advances in artificial intelligence (AI), particularly large language models (LLMs), have introduced new opportunities to enhance clinical decision-making. This review explores the current applications of AI technologies in oncologic treatment decision processes, with a focus on their potential integration into MDT-based decision-making for head and neck cancer. Furthermore, we introduce recent studies applying multi-agent LLM frameworks to MDT systems and discuss key challenges that must be addressed for successful clinical adoption. Ultimately, this review envisions an AI-augmented MDT model that enhances decision-making efficiency and objectivity, while enabling clinicians to focus more deeply on their core role—delivering optimal patient-centered cancer care.

Korean Society for Head and Neck OncologyVol. 41(2)
National Research Foundation, National Research Foundation of Korea, Ministry of Science and ICT, South Korea
Openalex Percentile: Top 69%
Artificial Intelligence in Healthcare and Education
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