MEMOIR-VLM hits 91.3% balanced accuracy on dementia classification with missing brain-scan inputs
PTenigma · x · 2026-10-07
A new paper published in Frontiers in Computational Neuroscience presents MEMOIR-VLM, which combines brain scans and clinical scores even when inputs are missing.
On held-out ADNI data, the model reached 91.3% balanced accuracy for distinguishing cognitively normal vs dementia, targeting Alzheimer's diagnostic support — an AI for Science / medical AI contribution.
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