External validation of deep learning algorithms for radiologic diagnosis: a systematic review
Purpose To assess generalizability of published deep learning (DL) algorithms for radiologic
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
diagnosis. Materials and Methods In this systematic review, the PubMed database was …
Deep learning-based diagnosis of Alzheimer's disease
Alzheimer's disease (AD), the most familiar type of dementia, is a severe concern in modern
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
healthcare. Around 5.5 million people aged 65 and above have AD, and it is the sixth …
An intelligent system for early recognition of Alzheimer's disease using neuroimaging
Alzheimer's disease (AD) is a neurodegenerative disease that affects brain cells, and mild
cognitive impairment (MCI) has been defined as the early phase that describes the onset of …
cognitive impairment (MCI) has been defined as the early phase that describes the onset of …
Reliable mutual distillation for medical image segmentation under imperfect annotations
Convolutional neural networks (CNNs) have made enormous progress in medical image
segmentation. The learning of CNNs is dependent on a large amount of training data with …
segmentation. The learning of CNNs is dependent on a large amount of training data with …
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 …
[HTML][HTML] Applications of artificial intelligence to aid early detection of dementia: a scoping review on current capabilities and future directions
Abstract Background & Objective With populations aging, the number of people with
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …
dementia worldwide is expected to triple to 152 million by 2050. Seventy percent of cases …
A review of deep transfer learning approaches for class-wise prediction of Alzheimer's disease using MRI images
Alzheimer's disease is an irreversible, progressive neurodegenerative disorder that destroys
the brain and memory functionalities. In Alzheimer's disease, the brain starts shrinking, and …
the brain and memory functionalities. In Alzheimer's disease, the brain starts shrinking, and …
Linear-depth quantum circuits for multiqubit controlled gates
AJ Da Silva, DK Park - Physical Review A, 2022 - APS
Quantum circuit depth minimization is critical for practical applications of circuit-based
quantum computation. In this work, we present a systematic procedure to decompose …
quantum computation. In this work, we present a systematic procedure to decompose …
An evolutionary explainable deep learning approach for Alzheimer's MRI classification
Abstract Deep Neural Networks (DNN) are prominent Machine Learning (ML) algorithms
widely used, especially in medical tasks. Among them, Convolutional Neural Networks …
widely used, especially in medical tasks. Among them, Convolutional Neural Networks …
Automatic detection of Alzheimer's disease using deep learning models and neuro-imaging: current trends and future perspectives
T Illakiya, R Karthik - Neuroinformatics, 2023 - Springer
Deep learning algorithms have a huge influence on tackling research issues in the field of
medical image processing. It acts as a vital aid for the radiologists in producing accurate …
medical image processing. It acts as a vital aid for the radiologists in producing accurate …