AIMC Topic: Animals

Clear Filters Showing 4441 to 4450 of 8866 articles

Machine-learning based prediction of Cushing's syndrome in dogs attending UK primary-care veterinary practice.

Scientific reports
Cushing's syndrome is an endocrine disease in dogs that negatively impacts upon the quality-of-life of affected animals. Cushing's syndrome can be a challenging diagnosis to confirm, therefore new methods to aid diagnosis are warranted. Four machine-...

WormPose: Image synthesis and convolutional networks for pose estimation in C. elegans.

PLoS computational biology
An important model system for understanding genes, neurons and behavior, the nematode worm C. elegans naturally moves through a variety of complex postures, for which estimation from video data is challenging. We introduce an open-source Python packa...

Overcoming Immunological Challenges Limiting Capsid-Mediated Gene Therapy With Machine Learning.

Frontiers in immunology
A key hurdle to making adeno-associated virus (AAV) capsid mediated gene therapy broadly beneficial to all patients is overcoming pre-existing and therapy-induced immune responses to these vectors. Recent advances in high-throughput DNA synthesis, mu...

Automated biomarker candidate discovery in imaging mass spectrometry data through spatially localized Shapley additive explanations.

Analytica chimica acta
The search for molecular species that are differentially expressed between biological states is an important step towards discovering promising biomarker candidates. In imaging mass spectrometry (IMS), performing this search manually is often impract...

Improving axial resolution in Structured Illumination Microscopy using deep learning.

Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
Structured Illumination Microscopy (SIM) is a widespread methodology to image live and fixed biological structures smaller than the diffraction limits of conventional optical microscopy. Using recent advances in image up-scaling through deep learning...

Hemopneumothorax detection through the process of artificial evolution - a feasibility study.

Military Medical Research
BACKGROUND: Tension pneumothorax is one of the leading causes of preventable death on the battlefield. Current prehospital diagnosis relies on a subjective clinical impression complemented by a manual thoracic and respiratory examination. These techn...

A deep neural network-based approach for prediction of mutagenicity of compounds.

Environmental science and pollution research international
We are exposed to various chemical compounds present in the environment, cosmetics, and drugs almost every day. Mutagenicity is a valuable property that plays a significant role in establishing a chemical compound's safety. Exposure and handling of m...

A primer on applying AI synergistically with domain expertise to oncology.

Biochimica et biophysica acta. Reviews on cancer
BACKGROUND: The concurrent growth of large-scale oncology data alongside the computational methods with which to analyze and model it has created a promising environment for revolutionizing cancer diagnosis, treatment, prevention, and drug discovery....

Semi-Automated Data Processing and Semi-Supervised Machine Learning for the Detection and Classification of Water-Column Fish Schools and Gas Seeps with a Multibeam Echosounder.

Sensors (Basel, Switzerland)
Multibeam echosounders are widely used for 3D bathymetric mapping, and increasingly for water column studies. However, they rapidly collect huge volumes of data, which poses a challenge for water column data processing that is often still manual and ...

Collective and synchronous dynamics of photonic spiking neurons.

Nature communications
Nonlinear dynamics of spiking neural networks have recently attracted much interest as an approach to understand possible information processing in the brain and apply it to artificial intelligence. Since information can be processed by collective sp...