AIMC Topic: Dogs

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Dog galloping on rough terrain exhibits similar limb co-ordination patterns and gait variability to that on flat terrain.

Bioinspiration & biomimetics
Understanding how animals regulate their gait during locomotion can give biological insight and inspire controllers for robots. Why animals use the gallop at the highest speeds remains incompletely explained. Hypothesized reasons for galloping includ...

Further evaluation and validation of the VETSCAN IMAGYST: in-clinic feline and canine fecal parasite detection system integrated with a deep learning algorithm.

Parasites & vectors
BACKGROUND: Fecal examinations in pet cats and dogs are key components of routine veterinary practice; however, their accuracy is influenced by diagnostic methodologies and the experience level of personnel performing the tests. The VETSCAN IMAGYST s...

Human-dog relationships as a working framework for exploring human-robot attachment: a multidisciplinary review.

Animal cognition
Robotic agents will be life-long companions of humans in the foreseeable future. To achieve such successful relationships, people will likely attribute emotions and personality, assign social competencies, and develop a long-lasting attachment to rob...

Machine-Learning-Based Approach to Decode the Influence of Nanomaterial Properties on Their Interaction with Cells.

ACS applied materials & interfaces
In an nanotoxicity system, cell-nanoparticle (NP) interaction leads to the surface adsorption, uptake, and changes into nuclei/cell phenotype and chemistry, as an indicator of oxidative stress, genotoxicity, and carcinogenicity. Different types of n...

Relationship between Machine-Learning Image Classification of T-Weighted Intramedullary Hypointensity on 3 Tesla Magnetic Resonance Imaging and Clinical Outcome in Dogs with Severe Spinal Cord Injury.

Journal of neurotrauma
Early prognostic information in cases of severe spinal cord injury can aid treatment planning and stratification for clinical trials. Analysis of intraparenchymal signal change on magnetic resonance imaging has been suggested to inform outcome predic...

AutoTune: Automatically Tuning Convolutional Neural Networks for Improved Transfer Learning.

Neural networks : the official journal of the International Neural Network Society
Transfer learning enables solving a specific task having limited data by using the pre-trained deep networks trained on large-scale datasets. Typically, while transferring the learned knowledge from source task to the target task, the last few layers...

Learning machine approach reveals microbial signatures of diet and sex in dog.

PloS one
The characterization of the microbial population of many niches of the organism, as the gastrointestinal tract, is now possible thanks to the use of high-throughput DNA sequencing technique. Several studies in the companion animals field already inve...

Challenges of machine learning model validation using correlated behaviour data: Evaluation of cross-validation strategies and accuracy measures.

PloS one
Automated monitoring of the movements and behaviour of animals is a valuable research tool. Recently, machine learning tools were applied to many species to classify units of behaviour. For the monitoring of wild species, collecting enough data for t...

Evaluation of the VETSCAN IMAGYST: an in-clinic canine and feline fecal parasite detection system integrated with a deep learning algorithm.

Parasites & vectors
BACKGROUND: Fecal examination is an important component of routine companion animal wellness exams. Sensitivity and specificity of fecal examinations, however, are influenced by sample preparation methodologies and the level of training and experienc...