Transformasi Layanan Telinga Hidung Tenggorokan–Kepala Leher (THT-KL) Melalui Artificial Intelligence: Literature Review

Rika Caesaria Hidayat

doi:10.62027/vitamedica.v4i3.810

Authors

Rika Caesaria Hidayat Institut Kesehatan Helvetia, Medan, Indonesia

DOI:

https://doi.org/10.62027/vitamedica.v4i3.810

Keywords:

artificial intelligence, deep learning, head and neck surgery, machine learning, otorhinolaryngology

Abstract

The development of Artificial Intelligence (AI) has driven a significant transformation in medical services, including in the field of Otorhinolaryngology–Head and Neck Surgery (ENT-HNS). This literature review aims to comprehensively analyze the utilization of AI in ENT-HNS services, covering diagnosis, medical imaging interpretation, disease detection, clinical decision-making, and implementation challenges. The method used is a narrative review of articles indexed in PubMed, Google Scholar, ScienceDirect, SpringerLink, and Wiley Online Library published between 2021–2026, in English and Indonesian. A total of 32 articles that met the inclusion criteria were analyzed. The results show that AI, especially machine learning and deep learning, has been widely applied for detecting chronic rhinosinusitis, otitis media, hearing loss, head and neck cancer, laryngeal disorders, and obstructive sleep apnea. AI also improves the accuracy of CT-scan and MRI interpretation through image segmentation, polyp detection, and tumor identification, while serving as a Clinical Decision Support System integrated with Electronic Medical Records. The main challenges include data privacy, ethics, dataset limitations, infrastructure, and workforce readiness. AI has strong potential to transform ENT-HNS services, although sustainable regulation, human resources, and evaluation are still required.

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