Integrated Diagnostics and Analytics (IDiA) Laboratory for Precision Medicine
Welcome to the IDiA Lab
The IDiA Lab develops artificial intelligence (AI), machine learning (ML), and statistical modeling approaches for translational applications in oncology and neurological disorders. Our primary focus is on advancing tools for disease prediction, prognosis, and treatment assessment across a range of diseases, including brain (adult and pediatric), lung, pancreatic, breast, and rectal cancers, as well as stroke, spine disease, and retinal disease. A key approach of our research is identifying radiomic (image-based) phenotypes from multi-modal medical imaging, including MRI, CT, and digital pathology slides, and exploring their associations with genomics (radiogenomics) and histopathology (radiopathomics) to enhance disease characterization, leveraging both traditional radiomic pipelines and foundation models trained on large-scale data.
We build AI tools that read medical images to advance disease prediction, prognosis, treatment assessment, and other clinical applications across oncology and neurology.
Radiomics
Quantitative image features that capture tumor heterogeneity the human eye can’t see.
Segmentation
Automatic outlining of tumors and organs on MRI, CT, and digital pathology slides.
Multimodal Learning
Fusing imaging, pathology, genomics, and clinical data for diagnosis and prognosis.
Survival Modeling
Risk scores that predict survival and progression from imaging and clinical data.
Foundation Models
Large pretrained models, built with self-supervised learning, that adapt to many tasks across cancer types.
Report Generation
Draft radiology reports generated directly from medical images.
Interested in Joining Us?
Work with us on AI tools that help predict disease, guide prognosis, and assess treatment response.
