In this study, a regularised convolutional neural network (CNN) with a modified XLNet
transformer is proposed as a unique way to divide and classify ovarian cancer. The …

One of the most crucial tasks of neurologists and radiologists is early brain tumor detection.
However, manually detecting and segmenting brain tumors from Magnetic Resonance …

Objective To construct a machine learning diagnostic model integrating feature
dimensionality reduction techniques and artificial neural network classifiers to develop the …

Purpose: Developing an artificial intelligence-based prostate cancer detection and
diagnosis system that can automatically determine important regions and accurately classify …

Breast cancer (BrCa) is the most common disease in women worldwide. Classifying the
BrCa image is extremely important for finding BrCa at an earlier stage and monitoring BrCa …

Ovarian Tumour is one of the common generally occurring tumours in females. Transvaginal
(US) ultrasonography is used as a screening examination to identify the appearance of …

Automatic analysis of pathological images is important for the diagnosis and treatment of
diseases. The use of computerized systems in this field is becoming increasingly common …

Abstract Medical Image Analysis (MIA) is one of the active research areas in computer
vision, where brain tumor detection is the most investigated domain among researchers due …

Early diagnosis of brain tumors plays an important role in a patient's treatment and makes it
easy to save his/her life. The conventional method of manually detecting brain tumors from …

A high mortality rate is associated with ovarian cancer, one of the most common types of
cancers in women. Ovarian cancer refers to a group of disorders that develop in the ovaries …