Meniere hastalığının teşhisinde Yapay Sistemler: Bir Derleme

Year 2025, Volume: 30 Issue: 1, 140 - 149, 29.01.2025

Huri Nur Coskun , Çağrı Yıldız , Ömer Faruk Çalım , Emrah Gündüz

https://doi.org/10.21673/anadoluklin.1555477

Abstract

Meniere Hastalığı (MH) spontan vertigo atakları, tek taraflı dalgalanan sensörinöral işitme kaybı, işitsel dolgunluk ve tinnitus ile karakterize karmaşık, multifaktöriyel bir iç kulak hastalığıdır. Endolenfatik hidrops (EH) genellikle MH’nin histopatolojik bir özelliği olarak kabul edilse de, 2015 tanı kılavuzları bunun varlığının tanı için gerekli olmadığını vurgulamaktadır. Manyetik Rezonans Görüntüleme (MRG), gelişim aşamasında olmasına rağmen EH’yi tespit etmek için değerli bir araç olarak ortaya çıkmıştır.
Son zamanlarda, insan bilişsel süreçlerini simüle eden ve hızla ilerleyen bir alan olan yapay zeka (YZ), MH çalışmalarında önemli bir ilgi görmüştür. Bu makale, Meniere Hastalığı’nın teşhisi, izlenmesi ve tedavisinde YZ ve derin öğrenmenin uygulanmasına ilişkin mevcut literatürü gözden geçirmektedir. İncelememiz PubMed, Scopus, Web of Science ve Science Direct’ten elde edilen yedi ilgili çalışmayı kapsamaktadır. Bunlar arasında dört makale, endolenfatik hidropsu tespit etmek ve ölçmek için MRG kullanımına odaklanmaktadır. Bu bulguları bir gelişim yörüngesi bağlamında sunuyor, mevcut metodolojilerin sınırlamalarını tartışıyor ve gelecekteki ilerlemeler için potansiyel yolları özetliyoruz.

Keywords

Derin öğrenme, endolenfatik hidrops, makine öğrenmesi, Meniere hastalığı, MikroRNA, yapay zeka

Artificial systems for the diagnosis of Meniere’s disease: A review

Abstract

Meniere’s Disease (MD) is a complex, multifactorial inner ear disorder characterized by episodes of spontaneous vertigo, unilateral fluctuating sensorineural hearing loss, aural fullness, and tinnitus. Although endolymphatic hydrops (EH) is often considered a histopathological hallmark of MD, the 2015 diagnostic guidelines emphasize that its presence is not essential for diagnosis. Magnetic Resonance Imaging (MRI) has emerged as a valuable tool for detecting EH, though it remains in a developmental phase.
Recently, artificial intelligence (AI)—a rapidly advancing field that simulates human cognitive processes—has garnered significant attention in the study of MD. This paper reviews the current literature on the application of AI and deep learning in the diagnosis, monitoring, and treatment of Meniere’s Disease. Our review encompasses seven relevant studies sourced from PubMed, Scopus, Web of Science, and ScienceDirect. Among these, four articles focus on the use of MRI to detect and quantify endolymphatic hydrops. We present these findings within the context of a development trajectory, discuss the limitations of current methodologies, and outline potential avenues for future advancements.

Keywords

Artificial intelligence, deep learning, endolymphatic hydrops, machine learning, MicroRNA

Ethical Statement

Ethics committee approval is not required for this study.

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