MBZUAI researchers led by Dr. Mohammad Yaqub are developing AI algorithms for real-time medical diagnoses, including tools for multiple sclerosis and congenital heart disease. The team developed ScanNav, an AI fetal anomaly assessment system licensed by GE Healthcare for Voluson SWIFT ultrasound machines. ScanNav assists doctors during anomaly scans after 20 weeks of gestation to check for conditions like heart issues and spina bifida. Why it matters: This research has the potential to significantly improve the speed and accuracy of medical diagnoses in the UAE and beyond, addressing critical gaps in healthcare.
MBZUAI's Dr. Mohammad Yaqub is developing AI algorithms to power point-of-care ultrasound (PoCUS) on mobile devices, expanding on his prior work on an AI-based fetal anomaly system used in GE Healthcare's ultrasound. These algorithms aim to make smaller, affordable PoCUS devices accessible in remote areas for faster diagnoses. The handheld devices, costing around $5000 USD, can connect to mobile devices and provide intelligence to interpret images, addressing the shortage of specialists in remote locations. Why it matters: This initiative democratizes access to critical diagnostic tools, potentially saving lives by enabling early detection of life-threatening conditions in underserved communities.
MBZUAI Associate Professor Mohammad Yaqub is focused on translating AI research into real-world healthcare solutions. His previous work includes the development of SanNav, an AI-based fetal anomaly detection system that became an FDA-approved product used by GE Healthcare and used on his own wife during pregnancy. Yaqub joined MBZUAI to help build a new model of AI research and education with a focus on interdisciplinary collaboration and industry partnerships. Why it matters: This highlights the UAE's growing focus on AI in healthcare and MBZUAI's role in bridging the gap between research and practical applications in the medical field.