Researchers have developed a machine learning algorithm to accurately detect heart murmurs in dogs, one of the main indicators of cardiac disease, which affects a large proportion of some smaller breeds such as King Charles Spaniels.
Specimens in a Cambridge museum will be brought to life through the power of Artificial Intelligence, by a team aiming to strengthen our connection with the natural world and reverse apathy towards biodiversity loss.
Two University alumni, Sir Demis Hassabis and Dr John Jumper, have been jointly awarded this year’s Nobel Prize in Chemistry for developing an AI model to solve a 50-year-old problem: predicting the complex structures of proteins.
Geoffrey Hinton, an alumnus of the University of Cambridge, was awarded the 2024 Nobel Prize in Physics, jointly with John Hopfield of Princeton University.
Researchers have developed a wearable ‘smart choker’ that uses a combination of flexible electronics and artificial intelligence techniques to allow people with speech impairments to communicate by detecting tiny movements in the throat.
Cambridge researchers are harnessing artificial intelligence to improve how forests are monitored. Associate Professor Dr Emily Lines and Research Associate Dr Harry Owen are using billions of laser-captured data points to measure biodiversity and make carbon accounting more accurate.
The Maxwell Centre at the University of Cambridge and SAS, leaders in data and AI, are launching a partnership aimed at accelerating healthcare innovation through enhanced access to advanced analytics.
New study proposes a framework for “Child Safe AI” following recent incidents which revealed that many children see chatbots as quasi-human and trustworthy.
Cambridge scientists have developed an artificially-intelligent tool capable of predicting in four cases out of five whether people with early signs of dementia will remain stable or develop Alzheimer’s disease.
Artificial intelligence (AI) could be used to identify drug resistant infections, significantly reducing the time taken for a correct diagnosis, Cambridge researchers have shown. The team showed that an algorithm could be trained to identify drug-resistant bacteria correctly from microscopy images alone.
© 2024 University of Cambridge