"The human brain is complex. Artificial intelligence (AI) machine learning and medical imaging data are accelerating breakthroughs in brain health, especially in medical diagnostics. A peer-reviewed study published today in Nature Neuroscience unveils an AI foundation model called BrainIAC (Brain Imaging Adaptive Core) that is capable of predicting brain age, dementia, time-to-stroke, and brain cancer from brain magnetic resonance imaging (MRI)."
"What sets this study apart is the generalizability of their AI foundation model. The traditional or narrow AI machine learning models are typically for a single purpose task and are often learned from small training datasets consisting of labeled data. Foundation models, on the other hand, are more flexible, general-purpose, and can perform a wide range of tasks, are pre-trained using self-supervised learning on massive"
BrainIAC is a foundation AI model pre-trained on 48,900 MRI scans using self-supervised learning. BrainIAC predicts brain age, dementia, time-to-stroke, and brain cancer from MRI data. BrainIAC consistently outperforms traditional supervised models and transfer learning from general biomedical imaging models across diverse downstream applications with minimal fine-tuning. BrainIAC generalizes across healthy and disease-containing scans. Foundation models offer flexibility for multiple medical tasks and perform better when pre-trained on large unlabeled imaging datasets. The model demonstrates potential to accelerate diagnostic capabilities and to extend machine learning utility across varied brain-health applications.
Read at Psychology Today
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