The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers - A Multidisciplinary Approach

Sep 21, 2026

Upload by Liam

Cancer remains a major global health burden, increasingly driven by genetic and metabolic abnormalities during disease onset. Skin cancer—encompassing squamous cell carcinoma, basal cell carcinoma, and melanoma—is rising worldwide and is strongly associated with ultraviolet radiation, while its metastatic potential makes early detection essential for effective therapy. This narrative review examines how artificial intelligence is being applied to diagnosing head and neck skin cancers from radiological and pathological viewpoints, highlighting progress from computational advances and radiomics, and emphasizing integration for improved patient outcomes.

LanguageEnglish

CategoryHealthcare

FormatPDF

Pages13

Reading Time33 min

AccessFree to download

Abstract

Keywords

1. Introduction

2. Skin Cancer Background and Risk Factors

diagnostics Review The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers: A Multidisciplinary Approach Zeliha Merve Semerci 1, Havva Serap Toru 2, *, Esra Çobankent Aytekin 3, Hümeyra Tercanlı 1, Diana Maria Chiorean 4,5, Yalçın Albayrak 6 and Ovidiu Simion Cotoi 4,5 Citation: Semerci, Z.M.; Toru, H.S.;Çobankent Aytekin, E.; Tercanlı, H.; Chiorean, D.M.; Albayrak, Y.; Cotoi, O.S. The Role of Artificial Intelligence in Early Diagnosis and Molecular Classification of Head and Neck Skin Cancers: A Multidisciplinary Approach. Diagnostics 2024, 14, 1477 . [https://doi.org/10.3390/](https://doi.org/10.3390/)[ ](https://doi.org/10.3390/)diagnostics14141477 Academic Editor: Dechang Chen Received: 31 May 2024 Revised: 1 July 2024 Accepted: 9 July 2024 Published: 10 July 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ([https://](https://)[ ](https://)[creativecommons.org/licenses/by/](creativecommons.org/licenses/by/)[ ](creativecommons.org/licenses/by/)[4.0/](4.0/)) . 1 Department of Oral and Maxillofacial Radiology, Faculty of Dentistry, Akdeniz University, 07070 Antalya, Turkey; [merveertugrul@outlook.com](merveertugrul@outlook.com) (Z.M.S.); [ysl_hmyr25@hotmail.com](ysl_hmyr25@hotmail.com) (H.T.) 2 Department of Pathology, Faculty of Medicine, Akdeniz University, 07070 Antalya, Turkey 3 Department of Pathology, Konya Numune Hospital, 42060 Konya, Turkey; [esracobankent@hotmail.com](esracobankent@hotmail.com) 4 Department of Pathology, County Clinical Hospital of Targu Mures, 540072 Targu Mures, Romania; [chioreandianamaria@yahoo.com](chioreandianamaria@yahoo.com) (D.M.C.); [ovidiu.cotoi@umfst.ro](ovidiu.cotoi@umfst.ro) (O.S.C.) 5 Department of Pathophysiology,“George Emil Palade” University of Medicine, Pharmacy, Science, and Technology of Targu Mures, 38 Gheorghe Marinescu Street, 540142 Targu Mures, Romania 6 Department of Electric and Electronic Engineering, Faculty of Engineering, Akdeniz University, 07010 Antalya, Turkey; [yalbayrak32@gmail.com](yalbayrak32@gmail.com) * Correspondence: [serap_toru@yahoo.com](serap_toru@yahoo.com) Abstract: Cancer remains a significant global health concern, with increasing genetic and metabolic irregularities linked to its onset. Among various forms of cancer, skin cancer, including squamous cell carcinoma, basal cell carcinoma, and melanoma, is on the rise worldwide, often triggered by ultraviolet (UV) radiation. The propensity of skin cancer to metastasize highlights the importance of early detection for successful treatment. This narrative review explores the evolving role of artificial intelligence (AI) in diagnosing head and neck skin cancers from both radiological and pathological perspectives. In the past two decades, AI has made remarkable progress in skin cancer research, driven by advances in computational capabilities, digitalization of medical images, and radiomics data. AI has shown significant promise in image-based diagnosis across various medical domains. In dermatology, AI has played a pivotal role in refining diagnostic and treatment strategies, including genomic risk assessment. This technology offers substantial potential to aid primary clinicians in improving patient outcomes. Studies have demonstrated AI’s effectiveness in identifying skin lesions, categorizing them, and assessing their malignancy, contributing to earlier interventions and better prognosis. The rising incidence and mortality rates of skin cancer, coupled with the high cost of treatment, emphasize the need for early diagnosis. Further research and integration of AI into clinical practice are warranted to maximize its benefits in skin cancer diagnosis and treatment. Keywords: head and neck neoplasms; artificial intelligence; skin neoplasms; diagnostic im

FAQs

Why is early diagnosis important for head and neck skin cancers?

Skin cancer can metastasize, making timely detection critical for successful treatment and improved prognosis.

Which skin cancer types are discussed as major categories?

The document distinguishes malignant melanoma and non-melanoma skin cancer, with non-melanoma further including basal cell carcinoma and squamous cell carcinoma.

How does artificial intelligence support diagnosis in this review?

The review highlights AI’s role in image-based diagnosis, including identifying and categorizing skin lesions and assessing malignancy, with growing use of radiomics and genomic risk assessment.

Sep 21, 2026

Upload by Liam