Researchers at Johns Hopkins are developing AI-driven video analysis tools to provide surgeons with unbiased skill assessments and personalized feedback. The system segments surgical procedures, detects instruments, and assesses skill in cataract surgery. Dr. Shameema Sikder is leading the development of technologies to improve ophthalmic surgical care standards internationally. Why it matters: AI-based surgical skill assessment could standardize training and improve patient outcomes in the region and globally.
Researchers have developed robotic path-planning and control algorithms for minimally invasive surgery (MIS) that steer flexible needles, incorporating teleoperation and haptic feedback. An AI algorithm was designed to predict target motion due to respiratory movement, improving needle placement accuracy. GANs were used to generate synthetic images visualizing organ and tumor motion. Why it matters: This research demonstrates the potential of AI and robotics to enhance precision and adaptability in MIS, potentially reducing patient trauma and improving recovery times in the region and beyond.
The inaugural Abu Dhabi AI-Robotics Conference was held at MBZUAI, focusing on AI-powered robotics to transform healthcare. Experts explored applications in microsurgery, biorobotics, and personalized treatment, with keynotes from H.E. Abdulla Abdulalee AlHumaidan, Timothy Baldwin, and Sami Haddadin. Dr. Hassa Al Mazrouei highlighted the potential for personalized care and automation driven by AI. Why it matters: The conference underscores the UAE's commitment to advancing AI and robotics in healthcare, potentially positioning the region as a leader in innovative medical technologies.
MBZUAI researchers are refining AI techniques to improve cancer diagnosis for colorectal and breast cancer, both common in the Middle East. They are using "few-shot tissue image generation," in which AI generates data for training AI models to recognize lesions, addressing the challenge of limited training data. The developed framework improves the efficiency of radiologists in breast cancer diagnosis, leading to better detection of breast lesions and timely treatment interventions. Why it matters: These advancements in AI-aided diagnostics can lead to earlier and more accurate cancer detection, ultimately improving patient outcomes in the region and beyond.
MBZUAI and Cleveland Clinic Abu Dhabi jointly showcased AI applications to address UAE healthcare challenges, focusing on diabetes, heart disease, and vision loss. The event highlighted AI-powered robots for surgical tool guidance, autonomous ultrasound systems, and AI-based eye diagnostics for early disease detection. Researchers presented advances in AI-powered intrabody navigation, robotic ultrasound imaging, and AI-based oculomics. Why it matters: These AI innovations have the potential to transform healthcare delivery in the UAE, improving surgical outcomes, democratizing access to diagnostic imaging, and enabling earlier disease detection.