AIMC Topic: Neural Networks, Computer

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CMFNet: a cross-dimensional modal fusion network for accurate vessel segmentation based on OCTA data.

Medical & biological engineering & computing
Optical coherence tomography angiography (OCTA) is a novel non-invasive retinal vessel imaging technique that can display high-resolution 3D vessel structures. The quantitative analysis of retinal vessel morphology plays an important role in the auto...

ECG-based machine learning model for AF identification in patients with first ischemic stroke.

International journal of stroke : official journal of the International Stroke Society
BACKGROUND: The recurrence rate of strokes associated with atrial fibrillation (AF) can be substantially reduced through the administration of oral anticoagulants. However, previous studies have not demonstrated a clear benefit from the universal app...

A Context-Dependent CNN-Based Framework for Multiple Sclerosis Segmentation in MRI.

International journal of neural systems
Despite several automated strategies for identification/segmentation of Multiple Sclerosis (MS) lesions in Magnetic Resonance Imaging (MRI) being developed, they consistently fall short when compared to the performance of human experts. This emphasiz...

Nongenerative Artificial Intelligence in Medicine: Advancements and Applications in Supervised and Unsupervised Machine Learning.

Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
The use of artificial intelligence (AI) within pathology and health care has advanced extensively. We have accordingly witnessed an increased adoption of various AI tools that are transforming our approach to clinical decision support, personalized m...

Development and validation of an AI-driven tool to evaluate chewing function: a proof of concept.

Journal of dentistry
BACKGROUND: Masticatory function is an important determinant of oral health and a contributing factor in the maintenance of general health. Currently, objective assessment of chewing function is a clinical challenge. Previously, several methods have ...

DCA-Enhanced Alzheimer's detection with shearlet and deep learning integration.

Computers in biology and medicine
Alzheimer's dementia (AD) is a neurodegenerative disorder that affects the central nervous system, causing the cells to stop working or die. The quality of life for individuals with AD steadily declines over time. While current treatments can relieve...

Attention and dilated convolutions inclusive deep-CNN with multiplexed texture features to diagnose Pathological and High Myopia.

Computers in biology and medicine
In today's era, precise and timely diagnosis of ocular diseases are crucial as these disorders jeopardize millions of visions. Early detection and proactive management can minimize vision threatening complications from these disorders. High Myopia(HM...

Voice Analysis in Dogs with Deep Learning: Development of a Fully Automatic Voice Analysis System for Bioacoustics Studies.

Sensors (Basel, Switzerland)
Extracting behavioral information from animal sounds has long been a focus of research in bioacoustics, as sound-derived data are crucial for understanding animal behavior and environmental interactions. Traditional methods, which involve manual revi...

Adapting to time: Why nature may have evolved a diverse set of neurons.

PLoS computational biology
Brains have evolved diverse neurons with varying morphologies and dynamics that impact temporal information processing. In contrast, most neural network models use homogeneous units that vary only in spatial parameters (weights and biases). To explor...

Neural networks with optimized single-neuron adaptation uncover biologically plausible regularization.

PLoS computational biology
Neurons in the brain have rich and adaptive input-output properties. Features such as heterogeneous f-I curves and spike frequency adaptation are known to place single neurons in optimal coding regimes when facing changing stimuli. Yet, it is still u...