Most of us think the clearest sign of Alzheimer's is memory loss. In fact, there are many different kinds of the degenerative disease. By failing to spot the tell-tale signs, many people are not diagnosed until much later. And, for the same reason, few people with less obvious signs of the disease are involved in clinical trials. The latest research from Northwestern University's Cognitive Neurology and Alzheimer's Disease Center is an attempt to change our preconceptions.
In a study, published earlier this month, researchers developed a machine-learning algorithm to detect Alzheimer's in brain scans 86 percent of the time. Even more impressively, it identified changes in the brain that showed mild cognitive impairment (MCI) 84 percent of the time. It might be able to identify these changes even earlier, but the researcher's only tested it on individual's who developed Alzheimer symptoms within nine years.
Artificial intelligence (AI) can identify Alzheimer's disease 10 years before doctors can discover the symptoms, according to new research. A team of researchers in Italy developed an algorithm that can spot structural changes in the brain that are caused by the disease a decade before the signs become apparent. The team from the University of Bari trained the AI by feeding in 67 MRI scans - 38 from Alzheimer's patients and 29 healthy patients - then asked it to analyse the neuronal connectivity to form an algorithm. Following the training, the AI was then asked to process brains from 148 subjects - 52 were healthy, 48 had Alzheimer's disease and 48 had mild cognitive impairment (MCI) but were known to have developed Alzheimer's disease two and a half to nine years later. According to the researchers, the AI diagnosed Alzheimer's disease 86 per cent of the time.
Researchers from across the country who collaborated on Alzheimer's Disease work may have found a way to detect the disease with a blood test before patients even exhibit symptoms. Alzheimer's is an incurable degenerative disease that impacts the brain causing confusion, memory loss and eventually leads to the loss of thinking skills that are key to simple task completion, according to the National Institute on Aging. Estimates put the Alzheimer's population in the United States around 5 million and suggest that the population will grow. The test actually does more than detect Alzheimer's, it can also distinguish between Alzheimer's, Parkinson's and regular control samples. This distinguishability is important because it means the test is sensitive to more than neurodegeneration which can be present with aging and other neurodegenerative diseases that might develop.
Artificial intelligence can be trained to spot structural changes in the brain linked to Alzheimer's disease nearly 10 years before doctors can diagnose it through symptoms, researchers claim. According to New Scientist, a team at the University of Bari in Italy has developed a machine learning algorithm that is able to spot alterations in how different regions of the brain are connected – alterations that could be early signs of the disease. Their algorithm was trained using MRI scans from 67 patients, 38 of which were from people affected by the disease and 29 from healthy patients. The scans came from the Alzheimer's Disease Neuroimaging Initiative database at the University of Southern California in Los Angeles. The AI was trained to correctly spot the difference between diseased and healthy brains, before being tested on its accuracy abilities on a second set of 148 scans – 52 of which were healthy, 48 had Alzheimer's and the other 48 had a mild cognitive impairment that was known to develop into Alzheimer's within 10 years.