The lab is affiliated with Mayo Clinic, AZ and ASU. Our members are computer scientists and clinical professionals with passion for AI.
Our focus is fusion of unstructured medical data (images, 3D models, clinical notes) for developing AI models to support clinical diagnosis and treatment.
We are particularly interested on the challenging aspect of longitudinal inference and how to construct a pathway to deploy the AI tools in the point-of-care to help to formulate strategies for prevention, screening, and treatment of cancer and cardiovascular disease.
Core research topic of our lab is: multimodal data fusion, anomaly detection, Large Language Model, AI fairness
We are also joint with Emory HITIlab
MedAI Journal club every week – joint with Stanford University, Emory University and NIH.
Collaborations: We have several multi-institutional research projects in collaboration with multiple academic centers and industries in US (including Stanford, MIT, Duke, SUNY Buffalo, Moffitt Cancer Center, UCSF, Philips healthcare, Carl Zeiss, Genetech, Arterys Inc) and Europe (CNR, Université Paris Descartes, HES-SO Valais) related to NLP and prediction. The application area of the developed methodologies spans from breast cancer, liver cancer, prostate cancer up to cardiovascular diseases, sepsis.
Competencies: Natural Language Processing (NLP), Computer Vision, Medical image analysis, deep learning, machine learning, Predictive modeling.
Open graduate student support and postdoc position in both Computer vision and NLP: please send CV and a letter of research interest to imon.banerjee[at]asu.edu
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