AIMC Topic: Dogs

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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...

Making Sense of Pharmacovigilance and Drug Adverse Event Reporting: Comparative Similarity Association Analysis Using AI Machine Learning Algorithms in Dogs and Cats.

Topics in companion animal medicine
Drug-associated adverse events cause approximately 30 billion dollars a year of added health care expense, along with negative health outcomes including patient death. This constitutes a major public health concern. The US Food and Drug Administratio...

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...

Bio-inspired robotic dog paddling: kinematic and hydro-dynamic analysis.

Bioinspiration & biomimetics
Research on quadrupedal robots inspired by canids or felids have been widely reported and demonstrated. However, none of these legged robots can deal with difficult environments that include water, such as small lakes, streams, rain, mud, flooded ter...

Deep learning enables rapid identification of potent DDR1 kinase inhibitors.

Nature biotechnology
We have developed a deep generative model, generative tensorial reinforcement learning (GENTRL), for de novo small-molecule design. GENTRL optimizes synthetic feasibility, novelty, and biological activity. We used GENTRL to discover potent inhibitors...

Neural Multimodal Cooperative Learning Toward Micro-Video Understanding.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The prevailing characteristics of micro-videos result in the less descriptive power of each modality. The micro-video representations, several pioneer efforts proposed, are limited in implicitly exploring the consistency between different modality in...

Using natural language processing and VetCompass to understand antimicrobial usage patterns in Australia.

Australian veterinary journal
BACKGROUND: Currently there is an incomplete understanding of antimicrobial usage patterns in veterinary clinics in Australia, but such knowledge is critical for the successful implementation and monitoring of antimicrobial stewardship programs.

A low-cost, automated parasite diagnostic system via a portable, robotic microscope and deep learning.

Journal of biophotonics
Manual hand counting of parasites in fecal samples requires costly components and substantial expertise, limiting its use in resource-constrained settings and encouraging overuse of prophylactic medication. To address this issue, a cost-effective, au...

Flow network tracking for spatiotemporal and periodic point matching: Applied to cardiac motion analysis.

Medical image analysis
The accurate quantification of left ventricular (LV) deformation/strain shows significant promise for quantitatively assessing cardiac function for use in diagnosis and therapy planning. However, accurate estimation of the displacement of myocardial ...