Deep learning (DL) is a powerful machine learning technique that has increasingly been
used to predict surgical outcomes. However, the large quantity of data required and lack of …

Simple Summary Machine learning in radiology of the central nervous system has seen
many interesting publications in the past few years. Since the focus has largely been on …

Background: Machine learning (ML) is now widely deployed in our everyday lives. Building
robust ML models requires a massive amount of data for training. Traditional ML algorithms …

Decision making on the treatment of vestibular schwannoma (VS) is mainly based on the
symptoms, tumor size, patient's preference, and experience of the medical team. Here we …

Physicians depend on their insight and experience and on a fundamentally indicative or
symptomatic approach to decide on the possible ailment of a patient. However, numerous …

Vestibular schwannomas (VS) are the most common tumor of the skull base with available
treatment options that carry a risk of iatrogenic injury to the facial nerve, which can …

Purpose Predicting the consistency of benign central nervous system (CNS) tumors prior to
surgery helps to improve surgical outcomes. This review summarizes and analyzes the …

This review presents a comprehensive history of Artificial Intelligence (AI) in the context of
the revolutionary application of machine learning (ML) to medical research and clinical …

The application of machine learning (ML) techniques to otolaryngology remains a topic of
interest and prevalence in the literature, though no previous articles have summarized the …

Simple Summary Due to the fact that they take inter-slice information into account, 3D-and
2.5 D-convolutional neural networks (CNNs) potentially perform better in tumor detection …