Neural Network Machine Learning for Determining Surgical Appropriateness in Head and Neck Subspecialty Referrals

Angeline Truong; John Paul Arios; Kevin Xin; Max L. Jiam; Nicole T. Jiam; Patrick K. Ha; Katherine C. Wai

doi:10.1177/01455613261438091

April 7, 2026Ear Nose & Throat JournalOpen Access

Neural Network Machine Learning for Determining Surgical Appropriateness in Head and Neck Subspecialty Referrals

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Key Points

This research aims to evaluate a machine learning tool for its effectiveness in determining surgical appropriateness for head and neck referrals.
Development of a neural network machine learning model.
External validation of the referral triage tool.
Assessment of the tool's impact on consultation times.
The tool successfully streamlined referral processes.
Expedited surgical consultations were observed.
Increased equitable access to head and neck cancer care was indicated.

Implication

External validation demonstrates potential to improve surgical consultation efficiency and access in head and neck cancer care.

Abstract

This externally validated tool demonstrates potential to streamline referral triage, expedite surgical consultation, and enhance equitable access to head and neck cancer care.

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Cite This Study

Truong et al. (2026) studied this question.

synapsesocial.com/papers/69d895be6c1944d70ce06cc4 https://doi.org/10.1177/01455613261438091

View Full Paper

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Neural Network Machine Learning for Determining Surgical Appropriateness in Head and Neck Subspecialty Referrals

Key Points

Implication

Abstract

Discussion

Cite This Study

Neural Network Machine Learning for Determining Surgical Appropriateness in Head and Neck Subspecialty Referrals

Key Points

Implication

Abstract

Discussion

Cite This Study

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