AIMC Topic: Horses

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Predicting Topographic Disease Progression and Treatment Response of Pegcetacoplan in Geographic Atrophy Quantified by Deep Learning.

Ophthalmology. Retina
PURPOSE: To identify disease activity and effects of intravitreal pegcetacoplan treatment on the topographic progression of geographic atrophy (GA) secondary to age-related macular degeneration quantified in spectral-domain OCT (SD-OCT) by automated ...

Assessing the utility value of Hucul horses using classification models, based on artificial neural networks.

PloS one
The aim of this study was to evaluate factors influencing the performance of Hucul horses and to develop a prediction model, based on artificial neural (AI) networks for predict horses' classification, relying on their performance value assessment du...

Incremental Ant-Miner Classifier for Online Big Data Analytics.

Sensors (Basel, Switzerland)
Internet of Things (IoT) environments produce large amounts of data that are challenging to analyze. The most challenging aspect is reducing the quantity of consumed resources and time required to retrain a machine learning model as new data records ...

Binary Horse herd optimization algorithm with crossover operators for feature selection.

Computers in biology and medicine
This paper proposes a binary version of Horse herd Optimization Algorithm (HOA) to tackle Feature Selection (FS) problems. This algorithm mimics the conduct of a pack of horses when they are trying to survive. To build a Binary version of HOA, or ref...

Cross-Modality Interaction Network for Equine Activity Recognition Using Imbalanced Multi-Modal Data.

Sensors (Basel, Switzerland)
With the recent advances in deep learning, wearable sensors have increasingly been used in automated animal activity recognition. However, there are two major challenges in improving recognition performance-multi-modal feature fusion and imbalanced d...

Improving Animal Monitoring Using Small Unmanned Aircraft Systems (sUAS) and Deep Learning Networks.

Sensors (Basel, Switzerland)
In recent years, small unmanned aircraft systems (sUAS) have been used widely to monitor animals because of their customizability, ease of operating, ability to access difficult to navigate places, and potential to minimize disturbance to animals. Au...

What can artificial intelligence and machine learning tell us? A review of applications to equine biomechanical research.

Journal of the mechanical behavior of biomedical materials
Artificial intelligence (AI) and machine learning (ML) are fascinating interdisciplinary scientific domains where machines are provided with an approximation of human intelligence. The conjecture is that machines are able to learn from existing examp...

Towards compound identification of synthetic opioids in nontargeted screening using machine learning techniques.

Drug testing and analysis
The constant evolution of the illicit drug market makes the identification of unknown compounds problematic. Obtaining certified reference materials for a broad array of new analogues can be difficult and cost prohibitive. Machine learning provides a...

Improving gait classification in horses by using inertial measurement unit (IMU) generated data and machine learning.

Scientific reports
For centuries humans have been fascinated by the natural beauty of horses in motion and their different gaits. Gait classification (GC) is commonly performed through visual assessment and reliable, automated methods for real-time objective GC in hors...