AIMC Topic: Animals

Clear Filters Showing 3731 to 3740 of 8866 articles

Phenotypic screening with deep learning identifies HDAC6 inhibitors as cardioprotective in a BAG3 mouse model of dilated cardiomyopathy.

Science translational medicine
Dilated cardiomyopathy (DCM) is characterized by reduced cardiac output, as well as thinning and enlargement of left ventricular chambers. These characteristics eventually lead to heart failure. Current standards of care do not target the underlying ...

Deep learning in veterinary medicine, an approach based on CNN to detect pulmonary abnormalities from lateral thoracic radiographs in cats.

Scientific reports
Thoracic radiograph (TR) is a complementary exam widely used in small animal medicine which requires a sharp analysis to take full advantage of Radiographic Pulmonary Pattern (RPP). Although promising advances have been made in deep learning for vete...

Neural mechanisms underlying the temporal organization of naturalistic animal behavior.

eLife
Naturalistic animal behavior exhibits a strikingly complex organization in the temporal domain, with variability arising from at least three sources: hierarchical, contextual, and stochastic. What neural mechanisms and computational principles underl...

Microrobotic Swarms for Intracellular Measurement with Enhanced Signal-to-Noise Ratio.

ACS nano
In cell biology, fluorescent dyes are routinely used for biochemical measurements. The traditional global dye treatment method suffers from low signal-to-noise ratios (SNR), especially when used for detecting a low concentration of ions, and increasi...

Resurrecting extinct cephalopods with biomimetic robots to explore hydrodynamic stability, maneuverability, and physical constraints on life habits.

Scientific reports
Externally shelled cephalopods with coiled, planispiral conchs were ecologically successful for hundreds of millions of years. These animals displayed remarkable morphological disparity, reflecting comparable differences in physical properties that w...

Is the use of deep learning an appropriate means to locate debris in the ocean without harming aquatic wildlife?

Marine pollution bulletin
With the global issue of marine debris ever expanding, it is imperative that the technology industry steps in. The aim is to find if deep learning can successfully distinguish between marine life and synthetic debris underwater. This study assesses w...

Single-cell specific and interpretable machine learning models for sparse scChIP-seq data imputation.

PloS one
MOTIVATION: Single-cell Chromatin ImmunoPrecipitation DNA-Sequencing (scChIP-seq) analysis is challenging due to data sparsity. High degree of sparsity in biological high-throughput single-cell data is generally handled with imputation methods that c...

Deep-fUS: A Deep Learning Platform for Functional Ultrasound Imaging of the Brain Using Sparse Data.

IEEE transactions on medical imaging
Functional ultrasound (fUS) is a rapidly emerging modality that enables whole-brain imaging of neural activity in awake and mobile rodents. To achieve sufficient blood flow sensitivity in the brain microvasculature, fUS relies on long ultrasound data...

Spectral organ fingerprints for machine learning-based intraoperative tissue classification with hyperspectral imaging in a porcine model.

Scientific reports
Visual discrimination of tissue during surgery can be challenging since different tissues appear similar to the human eye. Hyperspectral imaging (HSI) removes this limitation by associating each pixel with high-dimensional spectral information. While...

Closed-loop transcranial ultrasound stimulation with a fuzzy controller for modulation of motor response and neural activity of mice.

Journal of neural engineering
. We propose a closed-loop transcranial ultrasound stimulation (TUS) with a fuzzy controller to realize real-time and precise control of the motor response and neural activity of mice.. The mean absolute value (MAV) of the electromyogram (EMG) and pe...