Recent successes in image analysis with deep neural networks are achieved almost exclusively with Convolutional Neural Networks (CNNs), typically trained using the backpropagation (BP) algorithm. In a 2022 preprint, Geoffrey Hinton proposed the Forwa...
The prediction of Cervical Cancer (CC) remains a tough task due to diverse clinical variations and unbalanced data distribution, while good-quality data remains limited. Early CC signs tend to lack distinct characteristics, which makes their precise ...
Early identification of students' mental health issues has become an urgent priority in education and public health. However, existing studies often rely on questionnaire-based assessments or traditional machine learning models, which are limited by ...
The agriculture sector plays a pivotal role in the growth of the global economy, but remains highly susceptible to prediction errors, particularly in disease identification. To address the limitations of existing approaches, this study proposes a dee...
This study presents an automated system using Convolutional Neural Networks (CNNs) for segmenting FLAIR Magnetic Resonance Imaging (MRI) images to aid in the diagnosis of Multiple Sclerosis (MS). The dataset included 103 patients from Imam Khomeini H...
BACKGROUND: The aim of this systematic review is to compare the efficacy of convolutional neural networks (CNN) and Vision Transformers (ViT) in the field of dental imaging, in order to examine in depth the potential, advantages, and limitations of b...
Parkinson's disease (PD) is a prevalent and complex neurodegenerative disorder, with early diagnosis playing a critical role in timely treatment and management. Handwriting dynamics has emerged as a promising biomarker for early detection of PD, yet ...
BACKGROUND: The progression of cancer is driven by the accumulation of mutations in driver genes. Many researches promote to identify cancer driver genes. However, most of them ignore the high-order features in the network.
Parkinson's disease (PD) is a chronic neurodegenerative disorder characterized by progressive loss of dopaminergic neurons in substantia nigra, resulting in both motor impairments and cognitive decline. Traditional PD classification methods are exper...
Epidermal growth factor receptor (EGFR) overexpression is a key oncogenic driver in breast cancer, making it an important therapeutic target. Conventional approaches for EGFR identification, including motif- and homology-based methods, often lack acc...
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