Swati Shah Mody

Dr. Swati Shah Mody serves as a Clinical Associate Professor of Radiology at the University of Michigan Medical School, based at C.S. Mott Children's Hospital in Ann Arbor, Michigan. Previously, she held the position of Director of Pediatric Neuroradiology and Fetal Imaging at Children's Hospital of Michigan until her transition to the University of Michigan in 2022. Her clinical expertise centers on advanced pediatric imaging with specialized applications in neonatal and fetal diagnostics.

Her educational foundation includes:

• MBBS from University of Mumbai, Bombay (1987)
• DMRE from College of Physicians and Surgeons, Bombay (1990)
• MD from University of Mumbai (1991)
• Radiology Residency at Sir J J Group of Hospitals (1991)
• Senior Registrar in CT Scan/Neuroradiology at Bombay Hospital (1992)
• Radiology Residency at Wayne State University (1998)
• Pediatric Radiology Fellowship at Children's Hospital of Michigan/WSU (1999)

Dr. Mody's research program focuses intensely on Pediatric Neuroradiology with neonatal imaging specialization and Fetal-Placental Imaging, leveraging advanced MRI techniques and artificial intelligence. Her work bridges clinical radiology with computational innovation, particularly through her active involvement in the University of Michigan's e-Health and Artificial Intelligence Initiative. Current investigations include deep learning applications for neonatal brain scan analysis, high-field fetal-placental MR angiography, and outcome prediction modeling in neonatal encephalopathy.

Analysis of her 2022-2025 publications reveals a cohesive research trajectory prioritizing rare pediatric neurological conditions, advanced cardiac/fetal imaging, and AI-driven diagnostic solutions. Her work spans from case reports on infectious neuropathies to sophisticated 4D flow MRI characterization of vascular anomalies, demonstrating consistent methodological rigor while addressing critical gaps in pediatric diagnostic imaging.

Dr. Mody actively contributes to institutional governance through multiple committee appointments and maintains an open mentoring posture for trainees. Her Center Membership in the e-Health and Artificial Intelligence Initiative positions her at the forefront of medical AI integration, where she collaborates on developing clinical decision support systems for pediatric imaging interpretation.