AIMC Topic: Neural Networks, Computer

Clear Filters Showing 3521 to 3530 of 31376 articles

Deep learning-based aberration compensation improves contrast and resolution in fluorescence microscopy.

Nature communications
Optical aberrations hinder fluorescence microscopy of thick samples, reducing image signal, contrast, and resolution. Here we introduce a deep learning-based strategy for aberration compensation, improving image quality without slowing image acquisit...

Acquisition of similar properties by filters in the same stream of a multistream convolutional neural network.

Scientific reports
Functional modular organization is observed in a variety of cortical areas in the brain. In the visual cortex of primates, adjacent neurons often respond to the same visual submodality, such as color or orientation, and have a similar preferred orien...

Type 2 diabetes prediction method based on dual-teacher knowledge distillation and feature enhancement.

Scientific reports
Diabetes prediction is an important topic in the field of medical health. Accurate prediction can help early intervention and reduce patients' health risks and medical costs. This paper proposes a data preprocessing method, including removing outlier...

Drug discovery and mechanism prediction with explainable graph neural networks.

Scientific reports
Apprehension of drug action mechanism is paramount for drug response prediction and precision medicine. The unprecedented development of machine learning and deep learning algorithms has expedited the drug response prediction research. However, exist...

Recurrent models of orientation selectivity enable robust early-vision processing in mixed-signal neuromorphic hardware.

Nature communications
Mixed signal analog/digital neuromorphic circuits represent an ideal medium for reproducing bio-physically realistic dynamics of biological neural systems in real-time. However, similar to their biological counterparts, these circuits have limited re...

Varying pixel resolution significantly improves deep learning-based carotid plaque histology segmentation.

Scientific reports
Carotid plaques-the buildup of cholesterol, calcium, cellular debris, and fibrous tissues in carotid arteries-can rupture, release microemboli into the cerebral vasculature and cause strokes. The likelihood of a plaque rupturing is thought to be asso...

Dynamics of specialization in neural modules under resource constraints.

Nature communications
The brain is structurally and functionally modular, although recent evidence has raised questions about the extent of both types of modularity. Using a simple, toy artificial neural network setup that allows for precise control, we find that structur...

A deep multiple instance learning framework improves microsatellite instability detection from tumor next generation sequencing.

Nature communications
Microsatellite instability (MSI) is a critical phenotype of cancer genomes and an FDA-recognized biomarker that can guide treatment with immune checkpoint inhibitors. Previous work has demonstrated that next-generation sequencing data can be used to ...

Current status, challenges, and prospects of artificial intelligence applications in wound repair theranostics.

Theranostics
Skin injuries caused by physical, pathological, and chemical factors not only compromise appearance and barrier function but can also lead to life-threatening microbial infections, posing significant challenges for patients and healthcare systems. Ar...

The application of deep learning in early enamel demineralization detection.

PeerJ
OBJECTIVE: The study aims to develop a diagnostic model using intraoral photographs to accurately detect and classify early detection of enamel demineralization on tooth surfaces.