USC researchers used AI to analyze MRI scans and uncover the genetic architecture of the brain's corpus callosum.
Key Details
- 1Researchers analyzed brain MRI and genetic data from over 50,000 individuals worldwide.
- 2A novel AI tool was developed to automatically locate and measure the corpus callosum in MRI scans.
- 3Dozens of genetic regions affecting the size and thickness of the corpus callosum and subregions were identified.
- 4Distinct gene sets were found to govern area versus thickness, relating to brain function and development.
- 5The new AI tool is being made publicly available for research use, accelerating future discoveries.
Why It Matters
This research exemplifies the power of AI in large-scale neuroimaging analysis, connecting genetic factors to brain structure with direct implications for studying mental health and neurological disorders. Making the AI tool available to the community could further advance imaging genetics, precision diagnostics, and brain disease research.
Source
EurekAlert
Related News
•EurekAlert
AI Accelerates Radiopharmaceuticals, Boosts Personalized Dosimetry in Cancer
Machine learning is driving advancements in radiopharmaceutical drug discovery and optimizing patient-specific dosimetry for precision cancer therapy.
•EurekAlert
Physicians Overly Trust Erroneous AI, Ignore Contradictory Evidence
Physicians tend to trust incorrect AI advice, even when evidence contradicts it, suggesting risks in clinical decision-making with AI tools.
•EurekAlert
Concerns Raised Over Unverified Datasets in AI Health Prediction Models
A new study finds widely used AI health prediction models are built on datasets with unverifiable origins, raising safety and validity concerns.