Machine Learning in Clinical Diagnosis of Head and Neck Cancer-Reference-Cited by-同舟云学术

Machine Learning in Clinical Diagnosis of Head and Neck Cancer

Published:2024-09-14 Issue: Volume: Page:
ISSN:1749-4478
Container-title:Clinical Otolaryngology
language:en
Short-container-title:Clinical Otolaryngology

Author:

Black Hollie¹^ORCID,Young David²^ORCID,Rogers Alexander³^ORCID,Montgomery Jenny³^ORCID

Affiliation:

1. Department of Naval Architecture, Ocean and Marine Engineering University of Strathclyde Glasgow UK

2. Department of Mathematics and Statistics University of Strathclyde Glasgow UK

3. Department of Otolaryngology, Head and Neck Surgery Queen Elizabeth University Hospital Glasgow UK

Abstract

ABSTRACTObjectiveMachine learning has been effective in other areas of medicine, this study aims to investigate this with regards to HNC and identify which algorithm works best to classify malignant patients.DesignAn observational cohort study.SettingQueen Elizabeth University Hospital.ParticipantsPatients who were referred via the USOC pathway between January 2019 and May 2021.Main Outcome MeasuresPredicting the diagnosis of patients from three categories, benign, potential malignant and malignant, using demographics and symptoms data.ResultsThe classic statistical method of ordinal logistic regression worked best on the data, achieving an AUC of 0.6697 and balanced accuracy of 0.641. The demographic features describing recreational drug use history and living situation were the most important variables alongside the red flag symptom of a neck lump.ConclusionFurther studies should aim to collect larger samples of malignant and pre‐malignant patients to improve the class imbalance and increase the performance of the machine learning models.

Publisher

Wiley

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1111/coa.14220

Reference18 articles.

1. “Your urgent suspected cancer referral: Cancer Research UK ” (2022) https://www.cancerresearchuk.org/cancer‐symptoms/what‐is‐an‐urgent‐referral.

2. An open structure questionnaire on reasons for delay in presentation: a study of patients attending clinic with red flag symptoms of head and neck cancer

3. Outcomes of urgent suspicion of head and neck cancer referrals in Glasgow

4. T.Tikka K.Kavanagh A.Lowit et al. “Head and Neck Cancer Risk Calculator (HaNC‐RC)—v.2. Adjustments and Addition Of Symptoms and Social History Factors ” (2020).