AIMC Topic: Animals

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Deep learning applied to the segmentation of rodent brain MRI data outperforms noisy ground truth on full-fledged brain atlases.

NeuroImage
Translational magnetic resonance imaging of the rodent brain provides invaluable information for preclinical drug development. However, the automated segmentation of such images for quantitative analyses is limited compared to human brain imaging mai...

Rapid detection of poultry meat quality using S-band to KU-band radio-frequency waves combined with machine learning-A proof of concept.

Journal of food science
Rapid changes in consumer preferences for high-quality animal-based protein have driven the poultry industry to identify non-invasive, in-line processing technologies for rapid detection of muscle meat quality defects. At production plants, technolog...

Optimization of a passive roll absorber for robotic fish based on tune mass damper.

Bioinspiration & biomimetics
The robotic fish utilizes a bio-inspired undulatory propulsion system to achieve high swimming performance. However, significant roll motion has been observed at the head when the tail oscillates at certain frequencies, adversely affecting both perce...

Deep learning-based image classification of sea turtles using object detection and instance segmentation models.

PloS one
Sea turtles exhibit high migratory rates and occupy a broad range of habitats, which in turn makes monitoring these taxa challenging. Applying deep learning (DL) models to vast image datasets collected from citizen science programs can offer promisin...

Potential diagnostic biomarkers in heart failure: Suppressed immune-associated genes identified by bioinformatic analysis and machine learning.

European journal of pharmacology
Heart failure (HF) threatens tens of millions of people's health worldwide, which is the terminal stage in the development of majority cardiovascular diseases. Recently, an increasing number of studies have demonstrated that bioinformatics and machin...

Effect-directed analysis of genotoxicants in food packaging based on HPTLC fractionation, bioassays, and toxicity prediction with machine learning.

Analytical and bioanalytical chemistry
Many chemicals in food packaging can leach as complex mixtures to food, potentially including substances hazardous to consumer health. Detecting and identifying all of the leachable chemicals are impractical with current analytical instrumentation an...

Using machine learning to predict soil lead relative bioavailability.

Journal of hazardous materials
Although the relative bioavailability (RBA) can be applied to assess the effects of Pb on human health, there is no definition and no specific data of Pb-RBA to different soil sources and endpoints in vivo. In this study, we estimated the Pb-RBA from...

The evolution of patch-clamp electrophysiology: Robotic, multiplex, and dynamic.

Molecular pharmacology
The patch-clamp technique has been the gold standard for analysis of excitable cells. Since its development in the 1980s, it has contributed immensely to our understanding of neurons, muscle cells, and cardiomyocytes and the ion channels and receptor...

Classifying vocal responses of broilers to environmental stressors via artificial neural network.

Animal : an international journal of animal bioscience
Detecting early-stage stress in broiler farms is crucial for optimising growth rates and animal well-being. This study aims to classify various stress calls in broilers exposed to cold, heat, or wind, using acoustic signal processing and a transforme...

Research on machine vision online monitoring system for egg production and quality in cage environment.

Poultry science
In the domain of egg production, the application of automation technologies is essential for boosting productivity and quality. This study introduces an online monitoring system designed for egg quality assessment within caged environments, incorpora...