Convolutional neural networks (CNNs) constitute a widely used deep learning approach that
has frequently been applied to the problem of brain tumor diagnosis. Such techniques still …

Glioma represents a dominant primary intracranial malignancy in the central nervous
system. Artificial intelligence that mainly includes machine learning, and deep learning …

Medical Imaging (MI) plays a crucial role in healthcare, including disease diagnosis,
treatment, and continuous monitoring. The integration of non-invasive techniques such as X …

Chatter is an unstable and self-excited vibration that adversely affects part quality and tool
life in various machining processes. To achieve high-performance machining, chatter …

The early and effective diagnosis of Alzheimer's disease (AD) and mild cognitive impairment
(MCI) has received increasing attention in recent years. However, currently available deep …

Brain tumors pose a serious threat to public health, impacting thousands of individuals
directly or indirectly worldwide. Timely and accurate detection of these tumors is crucial for …

In medical facilities, the glioblastoma detection and growth patterns are critical yet
challenging tasks. It is important for early diagnosis and therapy planning to save lives …

Glioma grading is critical for treatment selection, and the fine classification between glioma
grades II and III is still a pathological challenge. Traditional systems based on a single deep …

The choice of treatment and prognosis evaluation depend on the accurate early diagnosis of
brain tumors. Many brain tumors go undiagnosed or are overlooked by clinicians as a result …

Brain tumour disease develops due to abnormal cell proliferation. The early identification of
brain tumours is vital for their effective treatment. Most currently available examination …