New test predicts dementia risk with 80% accuracy
A recent study has developed a test based on machine learning techniques capable of predicting the onset of dementia with a accuracy of up to 82%, and identifying the condition up to 9 years before diagnosis. The test relies on analyzing functional MRI images to monitor changes in the brain's default mode network, which are typically associated with disease progression—especially in individuals who showed no signs of dementia at the time of imaging but developed it later. The findings suggest that reduced connectivity in this network is linked to risk factors such as social isolation and genetic predisposition. This approach could be used for more precise monitoring of patients in the future. However, the study's results may be influenced by limitations related to test reproducibility and sample diversity. Currently, there are no preventive medications, but this test is expected to help select the most suitable participants for future treatments. Further research with diverse samples is necessary to improve its accuracy and validate its effectiveness.
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