A Systematic Review of ENT Disease Diagnostic Methods Using Edge AI Devices
Year: 2026
Type: review
Study design: Systematic Review
Abstract: This paper presents a systematic review of portable real-time systems designed for screening ear, nose, and throat (ENT) diseases using Artificial Intelligence (AI). Otitis media, sinusitis, nasal polyps, and throat infections are among the most frequently seen ENT conditions across all age groups, and without early detection they can develop into far more serious health problems. Current clinical methods put too much weight on the individual clinician's judgment, which sometimes lead to subjective diagnosis, and due to the lack of clinician in the underserved areas, the patients can be unable to get early treatment. The advent of high-resolution imaging combined with AI running directly on the embedded devices has opened the door to faster, more reliable screening where these results can back the diagnosis of the specialists as well. In this paper, we specifically presented an overview of the advances which were conducted in the ENT healthcare field within the last fourteen years and thoroughly discussed the literature in the chronological order to facilitate the research community.
Institution: Abu Dhabi University
Language: English
Topic: IoT and Edge/Fog Computing
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W7204277341