Awards and Recognitions
Research InterestsTraditional biology generally looks at only a few aspects of an organism at a time and attempts to molecularly dissect diseases and study them part by part with the hope that the sum of knowledge of parts would help explain the operation of the whole. Rarely has this been a successful strategy to understand the causes and cures for complex diseases. The motivation for a systems based approach to disease understanding aims to understand how large numbers of interrelated health variables, gene expression profiling, its cellular architecture and microenvironment, as seen in its histological image features, its 3 dimensional tissue architecture and vascularization, as seen in dynamic contrast enhanced (DCE) MRI, and its metabolic features, as seen by Magnetic Resonance Spectroscopy (MRS) or Positron Emission Tomography (PET), result in emergence of definable phenotypes. At the Center for Computational Imaging and Personalized Diagnostics (CCIPD) at Case Western Reserve University, we have been developing computerized knowledge alignment, representation, and fusion tools for integrating and correlating heterogeneous biological data spanning different spatial and temporal scales, modalities, and functionalities. These tools include computerized feature analysis methods for extracting subvisual attributes for characterizing disease appearance and behavior on radiographic (radiomics) and digitized pathology images (pathomics). Over the last 4 years our group has made substantialy progress in developing new radiomic and pathomic approaches for capturing intra-tumoral heterogeneity and modeling tumor appearance. Specifically we have shown how these radiomic and pathomic approaches can be applied to predicting disease outcome, recurrence, progression and response to therapy in the context of prostate, brain, rectal, oropharyngeal, and lung cancers.
Teaching InterestsMedical Image Analysis, Pattern Recognition and Scene Analysis, Numerical Modeling in Biomedical Systems, Biosignal Analysis and Biomedical Image Processing
Professional Leadership and Service
News About Anant Madabhushi
Case Western Reserve University signs license agreement to bring artificial intelligence breakthroughs closer to cancer patient care
When Case Western Reserve research showed that artificial intelligence (AI) could identify which lung cancer patients would benefit from chemotherapy, a national magazine called the finding one of the “10 Most Incredible Medical Breakthroughs of 2018.” Four years later, the university has signed an exclusive license agreement with Picture Health that aims to turn the promise of such AI tools into a reality that ultimately benefits patients around the globe.
A Case Western Reserve University-led team of scientists has used artificial intelligence (AI) to identify which patients with certain head and neck cancers would benefit from reducing the intensity of treatments such as radiation therapy and chemotherapy.
Case Western Reserve-led team to test artificial intelligence medical imaging to determine which rectal cancer patients need surgery—or can avoid it
CWRU announces the 2021 recipients for the Faculty Distinguished Research Awards
Artificial intelligence tool predicts treatment response and survival in small cell lung cancer patients
Researchers identify set of patterns from CT scans to help predict patient’s response to chemotherapy
Anant Madabhushi In the News
CWRU signs license agreement to bring AI closer to cancer care; UH marks 10 years of Harrington Discovery Institute
Anant Madabhushi, director of the Center for Computational Imaging and Personalized Diagnostics at Case School of Engineering, discussed a new exclusive license agreement between the university and Picture Health seeking to turn the promise of AI tools into a reality that ultimately benefits patients around the globe.