CLINICAL AI

The convergence of personal tragedy and technological innovation often produces the most compelling advances in healthcare. At the University of Alabama at Birmingham, this principle manifested in an unexpected way when Julie Schifanella, 56, her daughter Sophia, 23, and their mentor Laurie Tunagur became part of the first cohort to graduate from UAB's Graduate Certificate in AI in Medicine program this August.
The program represents more than traditional continuing education—it embodies UAB's ambitious vision to establish "the largest and most comprehensive program in AI in medicine, not just in the southeast or nationally, but globally" by 2025. The 15-credit certificate curriculum spans foundations of AI in medicine, practical applications, leadership and ethics, clinical workflow integration, and healthcare security and privacy. This comprehensive approach addresses the critical gap between technological capability and clinical implementation that has historically hindered AI adoption in healthcare settings.
What distinguishes this educational initiative is how personal motivation translates into innovative solutions. Julie's project focuses on developing an AI tool for early detection of brain viruses, inspired by her mother's death from a rare condition that took weeks to diagnose. Sophia's work targets improving quality of life for children with autism and their caregivers, drawing from her experience with her baby cousin's condition. These projects demonstrate how experiential learning, rooted in real clinical challenges, can drive meaningful innovation beyond theoretical knowledge acquisition.
The multi-generational participation pattern observed in this cohort reflects a broader strategic imperative for healthcare organizations. As Program Director Sandeep Bodduluri noted, "AI won't replace your job, but someone who knows how to use AI better just might". This reality necessitates comprehensive workforce development that spans career stages and professional roles. Laurie Tunagur's involvement as an executive assistant to hospital leadership exemplifies how AI literacy must extend beyond clinical roles to encompass operational and administrative functions.
This educational model addresses a fundamental challenge in healthcare AI implementation: the need to build organizational capacity that combines technical competency with clinical wisdom. By fostering multi-generational learning communities and encouraging project-based applications rooted in personal experience, UAB's approach suggests a pathway for healthcare institutions to develop AI-capable workforces while maintaining the human-centered focus that defines quality patient care.