Wales (Commonwealth Union) – Animal diseases have been a primary cause of concern, particularly for farmers. Historically, in certain times, animal diseases have been of equal concern as human diseases. Against this backdrop, researchers have formed a way of using artificial intelligence (AI) to identify parasites infecting animals in a faster technique.
The study from Aberystwyth University together with disease technology firm Techion has created and tested new machine learning tools that spontaneously identify the parasite implementing camera pictures. The finding may help farmers in Wales, and across the globe, identify infections faster and then make treatment quicker.
Liver and rumen flukes are parasites which cause diseases in grazing livestock worldwide, and cause loss of appetite, poorer body condition, and increases vulnerability to other infections. The parasites are of specific concern in Wales due to of the mild and wet climate. The new method will implement a device that can capture images from processed excreta at high magnification and the new development, which will mean that infections can be detected by farmers to get the results on the same day.
Dr Hefin Williams, Aberystwyth University’s Senior Lecturer in Agricultural Environment, stated that he believed this project is a vital milestone in changing and modernizing the diagnosis and management of these infections. The algorithms produced as a section of this project should make diagnosis more accessible and better. That means improved veterinary health outcomes and better sustainable agricultural businesses.
“The new technique may make it possible to diagnose these infections on farms, or even pen-side, and it does not need any expensive materials to perform. The current methods are labour intensive, require specialised skills and are time consuming. This limits their utility and their effectiveness to guide treatments as farmers often need ‘same day’ diagnosis to allow them to correctly treat a group of animals,” Dr Williams said.
The project was partially funded by the Welsh Government, together with the Wales Data Nation Accelerator.
