Researchers at the University of Cambridge, UK, have developed a new AI tool that predicts Alzheimer's disease progression with 82% accuracy from routinely collected cognitive tests and MRI scans. The ...

Scientists have used an AI model to reassess the results of a completed clinical trial for an Alzheimer's disease drug. They found that the drug slowed cognitive decline by 46% in a group of patients ...

Scientists said this made the AI tool almost three times more accurate at predicting progression from signs of early-stage dementia to Alzheimer’s disease than the current standard of care.

Scientists have used an AI model to reassess the results of a completed clinical trial for an Alzheimer's disease drug. They found the drug slowed ...

Please use one of the following formats to cite this article in your essay, paper or report: APA. Chaphalkar, Sushama R.. (2024, November 05). AI model predicts Alzheimer’s progression with new ...

Researchers have developed an AI tool that can predict with nearly 80% accuracy whether someone is at risk for developing Alzheimer’s disease based on their speech patterns.

For decades, Alzheimer’s disease has resisted nearly every significant pharmaceutical intervention. Despite billions invested ...

Researchers from the University of Cambridge’s Department of Psychology have developed a new AI model that outperforms current clinical tests in predicting the progression of Alzheimer's disease ...

New study shows AI machine learning can be used in the development of a biomarker based on a magnetic resonance imaging (MRI) scan for Alzheimer’s disease (AD).

Scientists from Duke, Harvard, and the University of Otago have unveiled a game-changing tool called DunedinPACNI. It uses a ...

While we remain skeptical of artificial intelligence's storytelling and filmmaking abilities, it is proving to have genuinely useful applications in science. As a new study shows, AI can even ...

The study sought to pinpoint the most relevant metabolic biomarkers associated with Alzheimer's disease, subsequently training AI models to predict the likelihood of disease occurrence or progression.