Artificial intelligence can pick up on symptoms of Alzheimer's disease in brain scans long before doctors or patients. A computer-driven algorithm was able to accurately foresee whether or not a person would develop Alzheimer's disease up to two years before he or she displays symptoms, according to a new study from McGill University. It was correct in its predictions 84% of the time. Researchers are excited for the AI's potential to help choose patients for clinical trials and drugs ahead of the disease's onset that could delay its debilitating effects. "If you can tell from a group of individuals who is the one that will develop the disease, one can better test new medications that could be capable or preventing the disease," Dr. Pedro Rosa-Neto, a study co-author, told Live Science.

Scientists then presented the algorithm with a new set of brain scans, some of which were from patients who currently had mild cognitive impairment. All of the scans, however, were taken before any of the patients had developed the disease. The algorithm was able to predict which patients would end up impaired with an accuracy of 84 percent. "This is an example how big data and open science brings tangible benefits to patient care," said Rosa-Neto to McGill News. The biggest benefit to patient care could be improved clinical trials studying the effectiveness of drugs for Alzheimer's, the most common form of dementia. "By using this tool, clinical trials could focus only on individuals with a higher likelihood of progressing to dementia within the time frame of the study," said Dr. Serge Gauthier, the study's co-lead author, to McGill News. "This will greatly reduce the cost and the time necessary to conduct these studies." Research was funded by the Canadian Consortium on Neurodegeneration in Aging (CCNA) and the Canadian Institutes of Health Research.

The algorithm -- which accurately predicted probable Alzheimer's disease 84 percent of the time -- could be particularly useful in selecting patients for clinical trials for drugs intended to delay disease onset, said lead study author Sulantha Sanjeewa, a computer scientist at McGill University in Canada. "If you can tell from a group of of individuals who is the one that will develop the disease, one can better test new medications that could be capable of preventing the disease," said co-lead study author Dr. Pedro Rosa-Neto, an associate professor of neurology, neurosurgery and psychiatry, also at McGill University. The technology is still in its early stages, but the findings suggest that AI analysis of brain scans could offer better results than relying on humans alone, Rosa-Neto told Live Science. The findings are detailed in a new study, which was published online in July in the journal Neurobiology of Aging. Developing drugs that slow the onset of Alzheimer's disease requires that the drugs be tested in clinical trials that run between 18 and 24 months, Rosa-Neto said.

Imagine if doctors could determine, many years in advance, who is likely to develop dementia. Such prognostic capabilities would give patients and their families time to plan and manage treatment and care. Thanks to artificial intelligence research conducted at McGill University, this kind of predictive power could soon be available to clinicians everywhere. Scientists from the Douglas Mental Health University Institute's Translational Neuroimaging Laboratory at McGill used artificial intelligence techniques and big data to develop an algorithm capable of recognizing the signatures of dementia two years before its onset, using a single amyloid PET scan of the brain of patients at risk of developing Alzheimer's disease. Their findings appear in a new study published in the journal Neurobiology of Aging.

Imagine if doctors could determine, many years in advance, who is likely to develop dementia. Such prognostic capabilities would give patients and their families time to plan and manage treatment and care. Thanks to artificial intelligence research conducted at McGill University, this kind of predictive power could soon be available to clinicians everywhere. Scientists from the Douglas Mental Health University Institute's Translational Neuroimaging Laboratory at McGill used artificial intelligence techniques and big data to develop an algorithm capable of recognizing the signatures of dementia two years before its onset, using a single amyloid PET scan of the brain of patients at risk of developing Alzheimer's disease. Their findings appear in a new study published in the journal Neurobiology of Aging.