AIMC Topic: Deep Learning

Clear Filters Showing 771 to 780 of 28423 articles

An optimized hybrid deep learning model to detect Alzheimer disease.

Scientific reports
Alzheimer's is a serious neurodegenerative disease that requires early detection for effective intervention. Traditional methods often struggle with accurately identifying the early stages, such as mild cognitive impairment (MCI), due to limitations ...

Artificial intelligence based platform for the automatic and simultaneous explainable detection of apnoea, oxygen desaturation, and artefacts in paediatric polygraphy exams (REST).

Scientific reports
The gold standard for the diagnosis of sleep apnoea (SA) is polysomnography, consisting of overnight in-lab tests, which are expensive for both patients and healthcare systems. Airflow and pulse/oximetry signals contain most of the necessary informat...

An advanced skin lesion segmentation and classification framework using deep learning strategies.

Scientific reports
Skin cancer is a deadly kind of cancer that grows rapidly and produces life-threatening issues within six weeks from the initial stage. Accurate analysis is needed for observing both the malignant and benign skin lesions that are more complicated to ...

Automatic detection of harmful cyanobacterial genera using deep CNN models and artemisinin optimization.

Scientific reports
Concerns over the spread of Cyanobacteria, which can lead to dangerous blooms that harm drinking water quality and, therefore, the health of plants and animals, are being raised by global warming. Traditional methods for assessing the amount of toxic...

Advanced MRI based Alzheimer's diagnosis through ensemble learning techniques.

Scientific reports
Alzheimer's Disease is a condition that affects the brain and causes changes in behavior and memory loss while making it hard to carry out tasks properly. It's vital to spot the illness early, for effective treatment. MRI technology has advanced in d...

Enhanced EfficientNet-Extended Multimodal Parkinson's disease classification with Hybrid Particle Swarm and Grey Wolf Optimizer.

Scientific reports
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...

Efficient and robust temporal processing with neural oscillations modulated spiking neural networks.

Nature communications
The brain exhibits rich dynamical properties that underpin its remarkable temporal processing capabilities. However, spiking neural networks (SNNs) inspired by the brain have not yet matched their biological counterparts in temporal processing and re...

A phase-aware Cross-Scale U-MAMba with uncertainty-aware segmentation and Switch Atrous Bifovea EfficientNetB7 classification of kidney lesion subtype.

Lasers in medical science
Kidney lesion subtype identification is essential for precise diagnosis and personalized treatment planning. However, achieving reliable classification remains challenging due to factors such as inter-patient anatomical variability, incomplete multi-...

Assessing the feasibility of deep learning-based attenuation correction using photon emission data inF-FDG images for dedicated head and neck PET scanners.

Biomedical physics & engineering express
This study aimed to evaluate the use of deep learning techniques to produce measured attenuation-corrected (MAC) images from non-attenuation-corrected (NAC) F-FDG PET images, focusing on head and neck imaging. A Residual Network (ResNet) was used to ...

An interpretable generative multimodal neuroimaging-genomics framework for decoding Alzheimer's disease.

Journal of neural engineering
Alzheimer's disease (AD) is the most prevalent form of dementia worldwide, encompassing a prodromal stage known as mild cognitive impairment (MCI), where patients may either progress to AD or remain stable. The objective of the work was to capture st...