Artificial Intelligence in Head and Neck Surgical Oncology: A State-of-the-Art Review

Artificial intelligence (AI) is rapidly reshaping head and neck surgical oncology by augmenting decision-making across the full perioperative continuum. This state-of-the-art review aims to provide head and neck surgical oncologists with a conceptual framework for understanding and critically appraising AI tools entering clinical practice, summarizing how machine learning, deep learning, and generative AI are being integrated into contemporary surgical workflows. Preoperative applications include detection of occult nodal metastasis and extranodal extension. Intraoperative innovations include augmented reality-assisted navigation, real-time margin assessment, and improving visual clarity and tissue handling for robotic platforms. Postoperatively, AI can predict complications like free flap failure and oncologic outcomes. Large language models are being operationalized for clinician-facing applications such as documentation and inbox support, as well as patient-facing education. Despite promising results, broad clinical deployment remains limited by concerns about privacy, validation, reliability, safety, and ethics. Widespread adoption will require prospective clinical trials, robust governance, and human-centered workflows that ensure AI remains a safe, assistive copilot.

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Publication Details

Journal
Journal of Clinical Medicine
Published
2026-04-06
DOI
https://doi.org/10.3390/jcm15072767
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00

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article

Artificial Intelligence in Head and Neck Surgical Oncology: A State-of-the-Art Review

Maria Feucht, Steven Chen, Janice L. Farlow, Aditya M Bhatt
Journal of Clinical Medicine
Artificial Intelligence in Healthcare and Education
article

Artificial Intelligence in Head and Neck Surgical Oncology: A State-of-the-Art Review

Maria Feucht, Steven Chen, Janice L. Farlow, Aditya M Bhatt
article en

Abstract

Artificial intelligence (AI) is rapidly reshaping head and neck surgical oncology by augmenting decision-making across the full perioperative continuum. This state-of-the-art review aims to provide head and neck surgical oncologists with a conceptual framework for understanding and critically appraising AI tools entering clinical practice, summarizing how machine learning, deep learning, and generative AI are being integrated into contemporary surgical workflows. Preoperative applications include detection of occult nodal metastasis and extranodal extension. Intraoperative innovations include augmented reality-assisted navigation, real-time margin assessment, and improving visual clarity and tissue handling for robotic platforms. Postoperatively, AI can predict complications like free flap failure and oncologic outcomes. Large language models are being operationalized for clinician-facing applications such as documentation and inbox support, as well as patient-facing education. Despite promising results, broad clinical deployment remains limited by concerns about privacy, validation, reliability, safety, and ethics. Widespread adoption will require prospective clinical trials, robust governance, and human-centered workflows that ensure AI remains a safe, assistive copilot.

Journal of Clinical MedicineVol. 15(7)
Indiana University – Purdue University Indianapolis (US)
Eli Lilly and Company
Openalex Percentile: Top 32%
Artificial Intelligence in Healthcare and Education
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