Age is more than just one number. While neuroscientists used to think of cognitive aging as a single trendline, they now realize that vast individual differences require a more predictive and personalized approach. As they uncover more factors that affect cognition over time, they are realizing that modeling the aging brain requires more diverse data … Read more
Worcester Polytechnic Institute (WPI) researchers have used a form of artificial intelligence (AI) to analyze anatomical changes in the brain and predict Alzheimer’s disease with nearly 93% accuracy. Their research, published in the journal Neuroscience, also revealed that the anatomical changes, involving loss of brain volume, differ by age and sex. Early diagnosis of Alzheimer’s … Read more
A team of Korean researchers has, for the first time in the world, developed a technology capable of enabling early diagnosis of major neurological disorders, including epilepsy, Parkinson’s disease, and schizophrenia, using only a small amount of saliva. This study was conducted jointly by a research team led by Dr. Sung-Gyu Park of the Advanced … Read more
New research warns that popular deep learning systems trained for cancer pathology may be relying on hidden shortcuts rather than genuine biological signals. Artificial intelligence tools are increasingly being developed to predict cancer biology directly from microscope images, promising faster diagnoses, and cheaper testing. But new research from the University of Warwick, published in Nature Biomedical … Read more
By harnessing everyday clinical assessments, researchers demonstrate that personalized 12-month forecasts of cognitive and functional change in dementia can be achieved without expensive imaging or invasive testing. Study design and analysis pipeline. Clinical assessments are collected at regular intervals throughout the Minder study (a), features used for statistical analysis and predictive modelling included clinical assessment … Read more
Approximately one in seven adults in the United States has kidney disease, where the organs responsible for filtering waste and excess water from the blood are damaged, according to the Centers for Disease Control and Prevention. Over time, this condition can lead to kidney failure, heart attack and stroke. But as many as 90% of people … Read more
Research in Aging Cell indicates that blood levels of particular small non-coding RNAs, which regulate gene expression, may influence how long a person lives. Investigators evaluated 828 small non-coding RNAs in blood samples from 1,271 community-dwelling older adults 71 years of age and older who were participating in an ongoing study. They then used machine … Read more
Current models of mortality risk after heart failure (HF) rely primarily on cardiac-specific clinical variables and may underestimate risk in elderly East Asian patients. Researchers from Japan used machine learning to analyze data from a nationwide registry of elderly HF patients. Their new model includes metrics of physical function and improved risk reclassification by about … Read more
Original story from the University of Tokyo A machine learning model that predicts insulin resistance implies a link to cancer. Insulin resistance – when the body doesn’t properly respond to insulin, a hormone that helps control blood glucose levels – is one of the fundamental causes of diabetes. In addition to diabetes, it is widely known … Read more
Researchers led by Xian-Yang Qin at the RIKEN Center for Integrative Medical Sciences (IMS) in Japan have developed a score that predicts the risk of liver cancer. Published in the scientific journal Proceedings of the National Academy of Sciences, the study establishes that the protein MYCN drives liver tumorigenesis, specifically of the type of tumors found … Read more