AIMC Topic: Dog Diseases

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Machine learning-based analyses support the existence of species complexes for and .

Parasitology
Human strongyloidiasis is a serious disease mostly attributable to Strongyloides stercoralis and to a lesser extent Strongyloides fuelleborni, a parasite mainly of non-human primates. The role of animals as reservoirs of human-infecting Strongyloides...

Sperm Tail Defects and Abnormal Testicular Blood Flow in a Beagle Dog: A Case Report.

Topics in companion animal medicine
A 5-year-old male Beagle dog produced ejaculates with a high percentage of spermatozoa with abnormal morphology, especially sperm tail defects. Although libido and semen volume were normal, ejaculates showed asthenospermia, oligozoospermia, and terat...

CNN-based diagnosis models for canine ulcerative keratitis.

Scientific reports
The purpose of this methodological study was to develop a convolutional neural network (CNN), which is a recently developed deep-learning-based image recognition method, to determine corneal ulcer severity in dogs. The CNN model was trained with imag...

Using machine learning to understand neuromorphological change and image-based biomarker identification in Cavalier King Charles Spaniels with Chiari-like malformation-associated pain and syringomyelia.

Journal of veterinary internal medicine
BACKGROUND: Chiari-like malformation (CM) is a complex malformation of the skull and cranial cervical vertebrae that potentially results in pain and secondary syringomyelia (SM). Chiari-like malformation-associated pain (CM-P) can be challenging to d...

Machine learning algorithm as a diagnostic tool for hypoadrenocorticism in dogs.

Domestic animal endocrinology
Canine hypoadrenocorticism (CHA) is a life-threatening condition that affects approximately 3 of 1,000 dogs. It has a wide array of clinical signs and is known to mimic other disease processes, including kidney and gastrointestinal diseases, creating...

A methodological approach for deep learning to distinguish between meningiomas and gliomas on canine MR-images.

BMC veterinary research
BACKGROUND: Distinguishing between meningeal-based and intra-axial lesions by means of magnetic resonance (MR) imaging findings may occasionally be challenging. Meningiomas and gliomas account for most of the total primary brain neoplasms in dogs, an...

Prediction of radiographic abnormalities by the use of bag-of-features and convolutional neural networks.

Veterinary journal (London, England : 1997)
This study evaluated the feasibility of bag-of-features (BOF) and convolutional neural networks (CNN) for computer-aided detection in distinguishing normal from abnormal radiographic findings. Computed thoracic radiographs of dogs were collected. For...

Development of a deep convolutional neural network to predict grading of canine meningiomas from magnetic resonance images.

Veterinary journal (London, England : 1997)
An established deep neural network (DNN) based on transfer learning and a newly designed DNN were tested to predict the grade of meningiomas from magnetic resonance (MR) images in dogs and to determine the accuracy of classification of using pre- and...

Prevalence and genotypes of Giardia lamblia from stray dogs and cats in Guangdong, China.

Veterinary parasitology, regional studies and reports
Giardia lamblia is a worldwide zoonotic intestinal parasite that infects humans and a wide range of mammals including dogs and cats, causing giardiasis with diarrhea. To investigate the infection and distribution of G. lamblia genotypes from stray do...