Spotting these clues may allow for lifestyle changes that could possibly delay the disease's destruction of the brain. "Improving the diagnostic accuracy of Alzheimer's disease is an important clinical goal. If we are able to increase the diagnostic accuracy of the models in ways that can leverage existing data such as MRI scans, then that can be hugely beneficial," explained corresponding author Vijaya B. Kolachalama, PhD, assistant professor of medicine at Boston University School of Medicine (BUSM). Using an advanced AI (artificial intelligence) framework based on game theory (known as generative adversarial network or GAN), Kolachalama and his team processed brain images (some low and high quality) to generate a model that was able to classify Alzheimer's disease with improved accuracy. Quality of an MRI scan is dependent on the scanner instrument that is used.
MRI scanners can map a person's innards in exquisite detail, but they say little about composition. Now, physicists are pushing MRI to a new realm of sensitivity to trace specific biomolecules in tissues, a capability that could aid in diagnosing Alzheimer's and other diseases. The advance springs not from improved scanners, but from better methods to solve a notoriously difficult math problem and extract information already latent in MRI data. Researchers are already using the new techniques to trace a fatty molecule called myelin in the brains of people with multiple sclerosis, mild cognitive impairment, and Alzheimer's disease. They also show that the scans can trace a molecule called proteoglycan in knee cartilage.
A'game-changing' eye scanner that can detect someone's biological age by examining the lens of their eye, has been developed by scientists. There is no universally accepted measure of biological ageing, according to the Boston University School of Medicine team, who built the scanner. The new, non-invasive technology, will allow researchers to find out someone's'true' or biological age, rather than how long they have been alive. According to the researchers, chronological age - how long you've been alive - does not adequately measure the rate someones body is actually ageing. They say that by knowing someone's biological age, and being able to track it throughout their life, can help in improving medical care.
There are currently developed algorithms for fractures and malignancies detection based on X-ray, CT and MRI image recognition. Also, there are a number of commercialized AI algorithms for predicting injury patterns and predicting postoperative complications following orthopedic and trauma procedures. This is one of the medical fields with the most abundant AI implementation. AI algorithms are being used for suicide prediction and for depression and anxiety treatment, a feature performed by chatbots. Used for early diagnostics of chronic diseases such as Multiple sclerosis, Alzheimer's disease, and Parkinson's disease, and for a number of acute neurological diseases such as brain tissue ischemia, intracranial hemorrhage, and hydrocephalus.
Another problem: as many as 30 percent of people enrolled in Alzheimer's studies based on symptoms didn't actually have the disease -- they had other forms of dementia or even other medical conditions. That doesn't give an accurate picture of whether a potential treatment might help, and the new definition aims to improve patient selection by using brain scans and other tests.