Simple Summary This study represents a resourceful review article that can deliver
resources on neurological diseases and their implemented classification algorithms to …

In computer vision, traditional machine learning (TML) and deep learning (DL) methods
have significantly contributed to the advancements of medical image analysis (MIA) by …

The classification of brain tumors is performed by biopsy, which is not usually conducted
before definitive brain surgery. The improvement of technology and machine learning can …

Nowadays, automatic disease detection has become a crucial issue in medical science due
to rapid population growth. An automatic disease detection framework assists doctors in the …

With the advancement in technology, machine learning can be applied to diagnose the
mass/tumor in the brain using magnetic resonance imaging (MRI). This work proposes a …

Understanding brain diseases such as categorizing Brain-Tumor (BT) is critical to assess the
tumors and facilitate the patient with proper cure as per their categorizations. Numerous …

Brain tumor classification is a challenging task in the field of medical image processing. The
present study proposes a hybrid method using Neutrosophy and Convolutional Neural …

Diabetes is an acute disease that happens when the pancreas cannot produce enough
insulin. It can be fatal if undiagnosed and untreated. If diabetes is revealed early enough, it …

The diagnosis and surgical resection using Magnetic Resonance (MR) images in brain
tumors is a challenging task to minimize the neurological defects after surgery owing to the …

Brain tumour detection is essential for improving patient survival and prospects. This
research work necessitates a physical examination with magnetic resonance imaging (MRI) …