Artificial Intelligence in Biomedical Imaging Lab (AIBIL)

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Mission Statement

The Artificial Intelligence in Biomedical Imaging Laboratory (AIBIL) focuses on development and application of machine learning and image analysis methods towards establishing imaging signatures of various diseases and disorders. These imaging signatures, based on both conventional machine learning and deep learning methods, aim to serve as individualized biomarkers for precision diagnosis and predictive modeling. The lab’s long standing record on use of machine learning in neuroimaging includes imaging signatures of brain aging, Alzheimer’s Disease, schizophrenia, and brain cancer, as well as of functional connectivity. Some of the current challenges and targets include dissecting disease heterogeneity using semi-supervised learning methods, establishing radiogenomic markers of genetic mutations, and relating imaging and pathology data.

Method

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Press

Second type of schizophrenia discovered

Machine Learning Identifies Personalized Brain Networks in Children

Researchers Discover Second Type of Schizophrenia