Medical image analysis using convolutional neural networks: a review
The science of solving clinical problems by analyzing images generated in clinical practice
is known as medical image analysis. The aim is to extract information in an affective and …
is known as medical image analysis. The aim is to extract information in an affective and …
Trustworthy artificial intelligence in Alzheimer's disease: state of the art, opportunities, and challenges
Abstract Medical applications of Artificial Intelligence (AI) have consistently shown
remarkable performance in providing medical professionals and patients with support for …
remarkable performance in providing medical professionals and patients with support for …
Multi-label classification of Alzheimer's disease stages from resting-state fMRI-based correlation connectivity data and deep learning
Alzheimer's disease is a neurodegenerative condition that gradually impairs cognitive
abilities. Recently, various neuroimaging modalities and machine learning methods have …
abilities. Recently, various neuroimaging modalities and machine learning methods have …
Transfer learning assisted classification and detection of Alzheimer's disease stages using 3D MRI scans
Alzheimer's disease effects human brain cells and results in dementia. The gradual
deterioration of the brain cells results in disability of performing daily routine tasks. The …
deterioration of the brain cells results in disability of performing daily routine tasks. The …
A CNN based framework for classification of Alzheimer's disease
In the current decade, advances in health care are attracting widespread interest due to their
contributions to people longer surviving and fitter lives. Alzheimer's disease (AD) is the …
contributions to people longer surviving and fitter lives. Alzheimer's disease (AD) is the …
Alzheimer detection using Group Grey Wolf Optimization based features with convolutional classifier
Alzheimer Detection (AD) is one of the most common memory depletion diseases that
occurs at an older age and is also, a widely recognized type of dementia. In this paper, we …
occurs at an older age and is also, a widely recognized type of dementia. In this paper, we …
A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data
M Chieregato, F Frangiamore, M Morassi, C Baresi… - Scientific reports, 2022 - nature.com
COVID-19 clinical presentation and prognosis are highly variable, ranging from
asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi …
asymptomatic and paucisymptomatic cases to acute respiratory distress syndrome and multi …
Early detection of cognitive decline using machine learning algorithm and cognitive ability test
Elderly people are the assets of the country and the government can ensure their peaceful
and healthier life. Life expectancy of individuals has expanded with technological …
and healthier life. Life expectancy of individuals has expanded with technological …
Diagnosis of Alzheimer's disease via an attention-based multi-scale convolutional neural network
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases. Accurate
diagnosis of mild cognitive impairment (MCI) in the prodromal stage of AD can delay onset …
diagnosis of mild cognitive impairment (MCI) in the prodromal stage of AD can delay onset …
A deep feature-based real-time system for Alzheimer disease stage detection
The origin of dementia can be largely attributed to Alzheimer's disease (AD). The
progressive nature of AD causes the brain cell deterioration that eventfully leads to physical …
progressive nature of AD causes the brain cell deterioration that eventfully leads to physical …