Improving diagnostic accuracy and treatment options for equine PPID. Equine Pituitary Pars Intermedia Dysfunction (PPID) is a common, chronic and potentially life-threatening disease of older horses and ponies. Although a treatment is available, the disease is poorly understood and there are some concerns that the current diagnostic technology is not delivering accurate results. Thus, this project aims to develop a more accurate diagnostic test for PPID, while exploring the relationship between ....Improving diagnostic accuracy and treatment options for equine PPID. Equine Pituitary Pars Intermedia Dysfunction (PPID) is a common, chronic and potentially life-threatening disease of older horses and ponies. Although a treatment is available, the disease is poorly understood and there are some concerns that the current diagnostic technology is not delivering accurate results. Thus, this project aims to develop a more accurate diagnostic test for PPID, while exploring the relationship between PPID and metabolic syndrome, to generate new insights into the cause and consequences of both diseases. As an added benefit, the project will assist horseracing laboratories to improve their detection methods for peptide doping in younger competition horses.
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Artificial intelligence algorithms to predict risk of injury in racehorses. This project will address the urgent need for predicting and preventing catastrophic and career limiting limb injuries and cardiac arrhythmias in racehorses due to over (or under) training. Using data from GPS and movement sensors integrated into saddlecloths, artificial intelligence algorithms will convert cumulative data on speed, gait, and stride characteristics during training, along with injury data, into a risk mat ....Artificial intelligence algorithms to predict risk of injury in racehorses. This project will address the urgent need for predicting and preventing catastrophic and career limiting limb injuries and cardiac arrhythmias in racehorses due to over (or under) training. Using data from GPS and movement sensors integrated into saddlecloths, artificial intelligence algorithms will convert cumulative data on speed, gait, and stride characteristics during training, along with injury data, into a risk matrix. Recorded heart rate and ECG data will also be analysed using artificial intelligence to detect early evidence of the development of cardiac arrhythmias. The system will improve racehorse welfare, providing a simple interface to warn trainers when risk of injury becomes high, in order to prevent catastrophic breakdown.Read moreRead less