Deep learning techniques, which use a massive technology known as convolutional neural
networks, have shown excellent results in a variety of areas, including image processing …

Objectives To review and compare the accuracy of convolutional neural networks (CNN) for
the diagnosis of meniscal tears in the current literature and analyze the decision-making …

Automatic seizure detection technology is of great significance to reduce workloads of
neurologists for epilepsy diagnosis and treatments. Imbalanced classification is a challenge …

Purpose More and more small brain metastases (BMs) in asymptomatic patients can be
detected even prior to their primary lung cancer with the development of MRI. The aim of this …

The early detection of posterior myocardial infarction (PMI) is an important task as it can
cause cardiac failure. Due to the absence of extra posterior leads in the standard 12-lead …

The increasing incidence of epilepsy has led to the need for automatic systems that can
provide accurate diagnoses in order to improve the life quality of people suffering from this …

Autism spectrum disorder as a condition has posed significant early diagnosis challenges to
the medical and health community for a long time. The early diagnosis of ASD is crucial for …

In the era of digitalization, the interaction between humans and machines, particularly in
Natural Language Processing, has gained crucial importance. This study focuses on …

Abstract Background Non-Coronavirus disease 2019 (COVID-19) pneumonia and COVID-
19 have similar clinical features but last for different periods, and consequently, require …

Cancer, the second largest human disease, has become a major public health problem. The
prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven …