By using a machine learning-based model, researchers accurately predicted the person at early stage of Alzheimer’s disease would remain stable or progress over time. The team suggests this prediction tool is easier to scale up and has a strong potential to transition to clinics globally. This would also help clinicians make more accurate and timely decisions on […]
Researchers in the Netherlands built a tool that could predict the time to a certain level of cognitive ability decline among people with mild cognitive impairment or mild dementia due to Alzheimer’s disease. They suggest that clinicians could use this tool to explain the expected natural decline of cognitive ability to patients. This could also help […]
People with preclinical Alzheimer’s disease have notably different gut microbiome features from those without the condition. The distinct gut microbiome features may help physicians detect preclinical Alzheimer’s early for individuals at risk. People with the preclinical condition have normal cognitive ability, while already show the biological evidence of Alzheimer’s in the brain, blood, or the […]
Researchers have found that by evaluating people’s blood levels of glial fibrillary acidic protein (GFAP), together with their cognitive test results and demographic information, they could predict Alzheimer’s disease at least 10 years before the diagnosis. The prediction was more accurate when they considered all these factors together, rather than considering the blood level of GFAP alone. […]
Researchers developed a machine learning model trained on a large amount of electronic health record data for finding risk factors that can predict Alzheimer’s disease. Machine learning model is a computer program that can find patterns in or make predictions about previously unseen data, after people trained it with a set of data. They identified weakened […]