Over the last decades, the field of medicine has witnessed significant progress in artificial
intelligence (AI), the Internet of Medical Things (IoMT), and deep learning (DL) systems …

Introduction: Convolutional neural networks (CNNs) represent a state-of-the-art
methodological technique in AI and deep learning, and were specifically created for image …

This study presents an up-to-date survey of the use of artificial intelligence (AI) in the field of
otorhinolaryngology, considering opportunities, research challenges, and research …

The advent of ChatGPT within the landscape of medical diagnostics, particularly in the
specialized area of head and neck disorders, exemplifies the confluence of artificial …

Middle and outer ear diseases are common otological diseases worldwide. Otoscopy and
otoendoscopy examinations are essential first steps in the evaluation of patients with …

The recent literature on AI in otological imaging is promising and demonstrates the future
potential of this technology in automating certain imaging tasks in a healthcare environment …

Purpose This PRISMA-compliant systematic review aims to analyze the existing applications
of artificial intelligence (AI), machine learning, and deep learning for rhinological purposes …

Artificial Intelligence (AI) has become a topic of interest that is frequently debated in all
research fields. The medical field is no exception, where several unanswered questions …

Due primarily to the excellent soft tissue contrast depictions provided by MRI, the
widespread application of head and neck MRI in clinical practice serves to assess various …

Systematic review of deep learning models in ultrasound tongue imaging for the detection
of speech disorders Page 1 P osted on 28 Apr 2020 — CC-BY 4.0 — h ttps://doi.org/10.36227/techrxiv.22699291.v1 …