AIMC Topic: Animals

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Architecture of the brain's visual system enhances network stability and performance through layers, delays, and feedback.

PLoS computational biology
In the visual system of primates, image information propagates across successive cortical areas, and there is also local feedback within an area and long-range feedback across areas. Recent findings suggest that the resulting temporal dynamics of neu...

Transfer of maternal immunity using a polyvalent vaccine and offspring protection in Nile tilapia, .

F1000Research
BACKGROUND: Vaccination is an effective and alternative means of disease prevention, however, it cannot be conducted on the offspring of fish. For this process to take place, the transfer of maternal immunity should be implemented. This study aims to...

A Novel Machine-Learning Framework Based on a Hierarchy of Dispute Models for the Identification of Fish Species Using Multi-Mode Spectroscopy.

Sensors (Basel, Switzerland)
Seafood mislabeling rates of approximately 20% have been reported globally. Traditional methods for fish species identification, such as DNA analysis and polymerase chain reaction (PCR), are expensive and time-consuming, and require skilled technicia...

Histological classification of canine and feline lymphoma using a modular approach based on deep learning and advanced image processing.

Scientific reports
Histopathological examination of tissue samples is essential for identifying tumor malignancy and the diagnosis of different types of tumor. In the case of lymphoma classification, nuclear size of the neoplastic lymphocytes is one of the key features...

Improving the classification of veterinary thoracic radiographs through inter-species and inter-pathology self-supervised pre-training of deep learning models.

Scientific reports
The analysis of veterinary radiographic imaging data is an essential step in the diagnosis of many thoracic lesions. Given the limited time that physicians can devote to a single patient, it would be valuable to implement an automated system to help ...

Accurate classification of major brain cell types using in vivo imaging and neural network processing.

PLoS biology
Comprehensive analysis of tissue cell type composition using microscopic techniques has primarily been confined to ex vivo approaches. Here, we introduce NuCLear (Nucleus-instructed tissue composition using deep learning), an approach combining in vi...

Classification of brain tumours from MRI images using deep learning-enabled hybrid optimization algorithm.

Network (Bristol, England)
Brain tumours are produced by the uncontrolled, and unusual tissue growth of brain. Because of the wide range of brain tumour locations, potential shapes, and image intensities, segmentation of the brain tumour by magnetic resonance imaging (MRI) is ...

Automated Cow Body Condition Scoring Using Multiple 3D Cameras and Convolutional Neural Networks.

Sensors (Basel, Switzerland)
Body condition scoring is an objective scoring method used to evaluate the health of a cow by determining the amount of subcutaneous fat in a cow. Automated body condition scoring is becoming vital to large commercial dairy farms as it helps farmers ...

Indirect Sensing of Subclinical Intramammary Infections in Dairy Herds with a Milking Robot.

Sensors (Basel, Switzerland)
This study determined the impact of subclinical intramammary infections (IMIs), such as the major and minor udder pathogens (MaPs and MiPs), on the somatic cell count (SCC) in cow milk and investigated the possibilities of indirect sensing of the udd...

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals.

Environmental research
Tissue-to-blood partition coefficients (P) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive...