This paper presents a comprehensive study of Convolutional Neural Networks (CNN) and
transfer learning in the context of medical imaging. Medical imaging plays a critical role in …

Artificial neural networks (ANNs) ability to learn, correct errors, and transform a large amount
of raw data into beneficial medical decisions for treatment and care has increased in …

Creating machines that behave and work in a way similar to humans is the objective of
artificial intelligence (AI). In addition to pattern recognition, planning, and problem-solving …

Recently, medical technologies have developed, and the diagnosis of diseases through
medical images has become very important. Medical images often pass through the …

To improve the accuracy of tumor identification, it is necessary to develop a reliable
automated diagnostic method. In order to precisely categorize brain tumors, researchers …

The COVID-19 pandemic has caused the death of many people around the world and has
also caused economic problems for all countries in the world. In the literature, there are …

A brain tumor refers to an abnormal growth of cells in the brain that can be either benign or
malignant. Oncologists typically use various methods such as blood or visual tests to detect …

Deep learning (DL) has made significant strides in medical imaging. This review article
presents an in-depth analysis of DL applications in medical imaging, focusing on the …

Irregular growth of cells in the skull is recognized as a brain tumor that can have two types
such as benign and malignant. There exist various methods which are used by oncologists …

The motive of job evaluation is to elucidate the relative work that the role of different jobs
makes towards different organisational objectives. Various methods are used to solve …