Workflow or Overload? | Radiology Rewired

Dr. Singh is a board-certified neuroradiologist and assistant professor at MUSC, where he completed his diagnostic radiology residency and neuroradiology fellowship, serving as chief resident in his final year. His expertise spans the full spectrum of diagnostic imaging, with a strong interest in stroke and brain tumor imaging, while also regularly interpreting general studies and performing a range of image-guided procedures.

A graduate of the Virginia Tech Carilion School of Medicine with dual undergraduate degrees in Human Nutrition and Biochemistry from Virginia Tech, Dr. Singh developed a deep interest in AI during training. He focuses on how AI can improve early disease detection, expand therapeutic imaging, enhance screening programs, and triage critical findings. He is particularly interested in the evolving role of radiologists as information integrators, combining AI insights with imaging, genomics, and clinical data to guide diagnosis and treatment.

Dr. Jeremy Heit is a Professor of Radiology and of Neurosurgery at Stanford University. He is a practicing neurointerventional radiologist who specializes in the diagnosis and minimally invasive treatment ofischemic and hemorrhagic stroke. Dr. Heit’s research group is working to understand the genetic, developmental, and pathophysiologic basis of cerebrovascular disease. In addition, his group is developing new minimally invasive, image- guided treatments for ischemic and hemorrhagic stroke. He has authored over 100 publications and is an investigator on multiple grants, including the CRISP 2 and DEFUSE 3 studies. He is the co-PI of the PRECISE basilar thrombectomy study.