[HTML][HTML] Lung nodule diagnosis and cancer histology classification from computed tomography data by convolutional neural networks: A survey
Lung cancer is among the deadliest cancers. Besides lung nodule classification and
diagnosis, developing non-invasive systems to classify lung cancer histological …
diagnosis, developing non-invasive systems to classify lung cancer histological …
Artificial intelligence for cognitive health assessment: state-of-the-art, open challenges and future directions
The subjectivity and inaccuracy of in-clinic Cognitive Health Assessments (CHA) have led
many researchers to explore ways to automate the process to make it more objective and to …
many researchers to explore ways to automate the process to make it more objective and to …
[Retracted] Classification of Alzheimer's Disease Using Gaussian‐Based Bayesian Parameter Optimization for Deep Convolutional LSTM Network
Alzheimer's disease (AD) is one of the most important causes of mortality in elderly people,
and it is often challenging to use traditional manual procedures when diagnosing a disease …
and it is often challenging to use traditional manual procedures when diagnosing a disease …
[Retracted] On Improved 3D‐CNN‐Based Binary and Multiclass Classification of Alzheimer's Disease Using Neuroimaging Modalities and Data Augmentation …
Alzheimer's disease (AD) is an irreversible illness of the brain impacting the functional and
daily activities of elderly population worldwide. Neuroimaging sensory systems such as …
daily activities of elderly population worldwide. Neuroimaging sensory systems such as …
An approach to binary classification of Alzheimer's disease using LSTM
In this study, we use LSTM (Long-Short-Term-Memory) networks to evaluate Magnetic
Resonance Imaging (MRI) data to overcome the shortcomings of conventional Alzheimer's …
Resonance Imaging (MRI) data to overcome the shortcomings of conventional Alzheimer's …
On disharmony in batch normalization and dropout methods for early categorization of Alzheimer's disease
Alzheimer's disease (AD) is a global health issue that predominantly affects older people. It
affects one's daily activities by modifying neural networks in the brain. AD is categorized by …
affects one's daily activities by modifying neural networks in the brain. AD is categorized by …
Brain-on-Cloud for automatic diagnosis of Alzheimer's disease from 3D structural magnetic resonance whole-brain scans
S Tomassini, A Sbrollini, G Covella, P Sernani… - Computer Methods and …, 2022 - Elsevier
Background and objective Alzheimer's disease accounts for approximately 70% of all
dementia cases. Cortical and hippocampal atrophy caused by Alzheimer's disease can be …
dementia cases. Cortical and hippocampal atrophy caused by Alzheimer's disease can be …
Alzheimer's disease diagnosis from single and multimodal data using machine and deep learning models: Achievements and future directions
Alzheimer's Disease (AD) is the most prevalent and rapidly progressing neurodegenerative
disorder among the elderly and is a leading cause of dementia. AD results in significant …
disorder among the elderly and is a leading cause of dementia. AD results in significant …
A comparison of machine learning techniques for the quality classification of molded products
The developments in the internet of things (IoT), artificial intelligence (AI), and cyber-physical
systems (CPS) are paving the way to the implementation of smart factories in what is …
systems (CPS) are paving the way to the implementation of smart factories in what is …
[HTML][HTML] Multi input–Multi output 3D CNN for dementia severity assessment with incomplete multimodal data
Alzheimer's Disease is the most common cause of dementia, whose progression spans in
different stages, from very mild cognitive impairment to mild and severe conditions. In clinical …
different stages, from very mild cognitive impairment to mild and severe conditions. In clinical …