AIMC Topic: Sheep

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Impact of functional electrical stimulation on nerve-damaged muscles by quantifying fat infiltration using deep learning.

Scientific reports
Quantitative imaging in life sciences has evolved into a powerful approach combining advanced microscopy acquisition and automated analysis of image data. The focus of the present study is on the imaging-based evaluation of the posterior cricoaryteno...

DeepOCR: A multi-species deep-learning framework for accurate identification of open chromatin regions in livestock.

Computational biology and chemistry
A wealth of experimental evidence has suggested that open chromatin regions (OCRs) are involved in many critical biological activities, such as DNA replication, enhancer activity, and gene transcription. Accurately identifying OCRs in livestock speci...

A Soft Robotic Actuator System for In Vivo Modeling of Normal Pressure Hydrocephalus.

IEEE transactions on bio-medical engineering
OBJECTIVE: The intracranial pressure (ICP) affects the dynamics of cerebrospinal fluid (CSF) and its waveform contains information that is of clinical importance in medical conditions such as hydrocephalus. Active manipulation of the ICP waveform cou...

The groundbreaking impact of digitalization and artificial intelligence in sheep farming.

Research in veterinary science
The integration of digitalization and Artificial Intelligence (AI) has marked the onset of a new era of efficient sheep farming in multiple aspects ranging from the general well-being of sheep to advanced web-based management applications. The result...

Extended-wavelength diffuse reflectance spectroscopy dataset of animal tissues for bone-related biomedical applications.

Scientific data
Diffuse reflectance spectroscopy (DRS) has been extensively studied in both preclinical and clinical settings for multiple applications, notably as a minimally invasive diagnostic tool for tissue identification and disease delineation. In this study,...

Characterization of lamb shashliks with different roasting methods by intelligent sensory technologies and GC-MS to simulate human muti-sensation: Based on multimodal deep learning.

Food chemistry
To simulate the functions of olfaction, gustation, vision, and oral touch, intelligent sensory technologies have been developed. Headspace solid-phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS) with electronic noses (E-noses...

Artificial intelligence (AI) for neurologists: do digital neurones dream of electric sheep?

Practical neurology
Artificial intelligence (AI) is routinely mentioned in journals and newspapers, and non-technical outsiders may have difficulty in distinguishing hyperbole from reality. We present a practical guide to help non-technical neurologists to understand he...

CT image segmentation of meat sheep Loin based on deep learning.

PloS one
There are no clear boundaries between internal tissues in sheep Computerized Tomography images, and it is difficult for traditional methods to meet the requirements of image segmentation in application. Deep learning has shown excellent performance i...

Predicting carcass tissue composition in Blackbelly sheep using ultrasound measurements and machine learning methods.

Tropical animal health and production
This study aimed to predict Blackbelly sheep carcass tissue composition using ultrasound measurements and machine learning models. The models evaluated were decision trees, random forests, support vector machines, and multi-layer perceptrons and were...

Artificial intelligence algorithm comparison and ranking for weight prediction in sheep.

Scientific reports
In a rapidly transforming world, farm data is growing exponentially. Realizing the importance of this data, researchers are looking for new solutions to analyse this data and make farming predictions. Artificial Intelligence, with its capacity to han...