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Research to study artificial intelligence use in cow diagnosis
The AI is able to track the motion of cows, as well as recognising each cow.

It will investigate if AI could detect disease earlier.

Researchers from the University of Bristol have received funding to study how artificial intelligence (AI) might be used to detect disease in dairy cows earlier.

The project is one of 14 to receive a share of £9m funding from the Biotechnology and Biological Sciences Research Council (BBSRC) and the Department of Environment, Food and Rural Affairs (Defra), in a move to combat endemic livestock disease.

The project, led by Professor Andrew Dowsey from Bristol Veterinary School, will see a collaboration of University of Bristol researchers in veterinary medicine, animal behaviour, computer vision and AI.

The group will use AI to monitor the social interactions of cattle to identify indications of developing mastitis or lameness, which are two of the most significant diseases affecting the UK dairy industry.

These diseases compromise the health and welfare of dairy cows, which can lead to financial losses for farmers and the industry. Cows that suffer from disease have also been found to contribute a higher proportion of methane emissions, affecting sustainability in the sector.

The current technology used for disease detection in dairy cows tends to focus on observable symptoms that are associated with later stages of the disease.

Professor Dowsey and the research team will be investigating whether AI can monitor social interactions to identify diseases at an earlier stage.

Previous studies have recognised a correlation between cattle in the early stages of disease and reduced levels of social interaction. However, farmers are frequently too busy to closely monitor social interactions between their cows.

The AI developed by the research team is able to track the motion of cows, as well as recognising each cow by its distinctive coat pattern.

Once the AI has been trained to spot behaviour changes that indicate early-stage mastitis and lameness, it will be deployed to recruited farms for testing.

Professor Dowsey said: “We are excited to have been given the opportunity to fuse Bristol Veterinary School’s world-class expertise in animal behaviour with our recent developments in artificial intelligence for livestock monitoring.

“Detecting subtle changes in social behaviour could hold the key to the early diagnosis of disease in dairy cattle."

Image (C) Shutterstock

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Practices urged to audit neutering data

News Story 1
 RCVS Knowledge has called on vet practices to audit their post-operative neutering outcomes.

It follows the release of the 2024 NASAN benchmarking report, which collates data from neutering procedures performed on dogs, cats and rabbits.

The benchmarking report enables practices in the UK and Ireland to compare their post-operative outcomes to the national average. This includes the rate of patients lost to follow-up, which in 2024 increased to 23 per cent.

Anyone from the practice can submit the data using a free template. The deadline for next report is February 2026.

Visit the RCVS Knowledge website to complete an audit. 

Click here for more...
News Shorts
UK's BSE risk status downgraded

The WOAH has downgraded the UK's international risk status for BSE to 'negligible'.

Defra says that the UK's improved risk status recognises the reputation for having the highest standards for biosecurity. It adds that it demonstrates decades of rigorous animal control.

Outbreaks of Bovine Spongiform Encephalopathy, also known as mad cow disease, have previously resulted in bans on Britain's beef exports.

The UK's new status could lead to expanded trade and better confidence in British beef.

Christine Middlemiss, the UK's chief veterinary officer, said: "WOAH's recognition of the UK as negligible risk for BSE is a significant milestone and is a testament to the UK's strong biosecurity measures and the hard work and vigilance of farmers and livestock keepers across the country who have all played their part in managing the spread of this disease.