AIMC Topic: Animals

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Identification of parameters and formulation of a statistical and machine learning model to identify Babesia canis infections in dogs using available ADVIA hematology analyzer data.

Parasites & vectors
BACKGROUND: Canine babesiosis is an important tick-borne disease in endemic regions. One of the relevant subspecies in Europe is Babesia canis, and it can cause severe clinical signs such as hemolytic anemia. Apart from acute clinical symptoms dogs c...

Validation of a deep learning-based image analysis system to diagnose subclinical endometritis in dairy cows.

PloS one
The assessment of polymorphonuclear leukocyte (PMN) proportions (%) of endometrial samples is the hallmark for subclinical endometritis (SCE) diagnosis. Yet, a non-biased, automated diagnostic method for assessing PMN% in endometrial cytology slides ...

Positional SHAP (PoSHAP) for Interpretation of machine learning models trained from biological sequences.

PLoS computational biology
Machine learning with multi-layered artificial neural networks, also known as "deep learning," is effective for making biological predictions. However, model interpretation is challenging, especially for sequential input data used with recurrent neur...

Disease-Specific Imaging Utilizing Support Vector Machine Classification of H-Scan Parameters: Assessment of Steatosis in a Rat Model.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
In medical imaging, quantitative measurements have shown promise in identifying diseases by classifying normal versus pathological parameters from tissues. The support vector machine (SVM) has shown promise as a supervised classification algorithm an...

Deep Learning Empowered Wearable-Based Behavior Recognition for Search and Rescue Dogs.

Sensors (Basel, Switzerland)
Search and Rescue (SaR) dogs are important assets in the hands of first responders, as they have the ability to locate the victim even in cases where the vision and or the sound is limited, due to their inherent talents in olfactory and auditory sens...

Decoding alarm signal propagation of seed-harvester ants using automated movement tracking and supervised machine learning.

Proceedings. Biological sciences
Alarm signal propagation through ant colonies provides an empirically tractable context for analysing information flow through a natural system, with useful insights for network dynamics in other social animals. Here, we develop a methodological appr...

Overcoming challenges in extracting prescribing habits from veterinary clinics using big data and deep learning.

Australian veterinary journal
Understanding antimicrobial usage patterns and encouraging appropriate antimicrobial usage is a critical component of antimicrobial stewardship. Studies using VetCompass Australia and Natural Language Processing (NLP) have demonstrated antimicrobial ...

Integrated deep learning framework for accelerated optical coherence tomography angiography.

Scientific reports
Label-free optical coherence tomography angiography (OCTA) has become a premium imaging tool in clinics to obtain structural and functional information of microvasculatures. One primary technical drawback for OCTA, however, is its imaging speed. The ...

Updates in Laparoscopy.

The Veterinary clinics of North America. Small animal practice
Minimally invasive surgery continues to be an active area of experimental and clinical research in veterinary medicine. The advances we make in this field correspond to multiple benefits for our patients. New MIS approaches (retroperitoneal, NOTES, r...

High-throughput segmentation of unmyelinated axons by deep learning.

Scientific reports
Axonal characterizations of connectomes in healthy and disease phenotypes are surprisingly incomplete and biased because unmyelinated axons, the most prevalent type of fibers in the nervous system, have largely been ignored as their quantitative asse...