Research Interests: AI-based Cancer Diagnosis and Prognosis, AI for Precision Medicine, AI for Accessible Healthcare, Human Centered AI in Radiology, Machine Learning for Medical Imaging, Radiomics
Dr. Khalvati’s research program is focussed on the design and development of Artificial Intelligence (AI) solutions for Medical Imaging and Precision Medicine. He leads the design, discovery, and validation of AI-based quantitative imaging biomarkers (radiomics) for diagnosis and prognosis of different cancer sites (e.g., brain) with the goal of delivering precision medicine and compassionate healthcare to patients. The motivation for his research is that as a non-invasive alternative to biopsy for studying cancer, AI-powered Medical Imaging can capture the entirety of cancer site with distinct advantage of assessing tissue heterogeneity. The hypothesis is that AI-driven and radiomic biomarkers have the potential to uncover latent diagnostic and prognostic information encoded in medical images which may replace or complement biopsy-driven biomarkers such as pathology and genomics signatures. One aspect of Dr. Khalvati’s research is to design and implement joint Radiologist-AI decision making solutions, which will significantly advance our understanding of how AI algorithms findings can be translated from mere information to practical meaning, and how that meaning can be properly communicated to clinicians in order to significantly improve the accuracy of final diagnoses, prognoses, and treatment planning with a direct impact on the quality of care given to patients.