Globally, there is a substantial unmet need to diagnose various diseases effectively. The
complexity of the different disease mechanisms and underlying symptoms of the patient …

Alzheimer's disease (AD) is the most common chronic disease in the elderly, with a high
incidence rate. In recent years, deep learning has become popular in the field of medical …

Alzheimer's Disease (AD) is a chronic neurodegenerative disease without effective
medications or supplemental treatments. Thus, predicting AD progression is crucial for …

Identifying Alzheimer's disease (AD) involves a deliberate diagnostic process owing to its
innate traits of irreversibility with subtle and gradual progression. These characteristics make …

Alzheimer's disease (AD) is a deadly cognitive condition in which people develop severe
dementia symptoms. Neurologists commonly use a series of physical and mental tests to …

Age-associated diseases rise as life expectancy increases. The brain presents age-related
structural changes across life, with different extends between subjects and groups. During …

High impedance faults caused by vegetation are difficult to detect when covered conductors
in medium voltage overhead power lines are used. Long-term contact of XLPE insulation …

Magnetic resonance imaging (MRI) of the brain has benefited from deep learning (DL) to
alleviate the burden on radiologists and MR technologists, and improve throughput. The …

Alzheimer's disease, which is characterized by a continual deterioration of cognitive abilities
in older people, is the most common form of dementia. Neuroimaging data, for example …

Background The combination of anatomical MRI and deep learning‐based methods such as
convolutional neural networks (CNNs) is a promising strategy to build predictive models of …