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

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 …

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 …

Objective Diagnosis of otosclerosis on temporal bone CT images is often difficult because
the imaging findings are frequently subtle. Our aim was to assess the utility of deep learning …

Convolutional neural network (CNN), a class of artificial neural networks that has become
dominant in various computer vision tasks, is attracting interest across a variety of domains …

Deep learning has rapidly advanced in various fields within the past few years and has
recently gained particular attention in the radiology community. This article provides an …

Objectives/Hypothesis There may be an interobserver variation in the diagnosis of laryngeal
disease based on laryngoscopic images according to clinical experience. Therefore, this …

Background An important challenge of big data is using complex information networks to
provide useful clinical information. Recently, machine learning, and particularly deep …

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 …

Materials and Methods: Scientific databases including PubMed, Science Direct, Web of
Science, JSTOR, and Google Scholar were used to search for relevant literature on DCNN …