Researchers from KAUST, King Faisal Specialist Hospital, and collaborators have developed a new method to predict cardiometabolic disease risk in underrepresented ethnic populations using genetic information and public databases. The study focused on Arab communities and created a framework to determine polygenic scores for more accurate heart disease prediction. The framework was validated using records of over 5,000 Arab patients, demonstrating that genetic risk complements conventional risk factors. Why it matters: This research addresses a critical gap in genomic data for non-European populations, potentially leading to more effective and personalized healthcare strategies in the Arab world 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.
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 and Abu Dhabi Health Services Company (SEHA) are collaborating to develop AI algorithms to predict heart attacks months in advance with 87% accuracy using ultrasound images. The project aims to preemptively predict heart attacks in the short and long term, addressing the high rates of cardiac arrest, especially in the Middle East. A Memorandum of Understanding (MoU) was signed between SEHA and MBZUAI to integrate AI into healthcare. Why it matters: This partnership could significantly improve healthcare outcomes in the region by leveraging AI to proactively address heart disease, a leading cause of death.
Researchers at Khalifa University have developed an AI system capable of predicting cardiovascular disease (CVD) risks up to 12 years in advance. The AI model uses data from the Framingham Heart Study to assess long-term CVD risk factors. It outperforms existing methods in predicting CVD incidence over extended periods. Why it matters: This advancement could significantly improve preventative healthcare strategies in the UAE and globally by enabling earlier interventions for individuals at high risk of heart disease.
A senior lecturer at the University of New South Wales discussed the use of AI to improve early prognosis and personalized treatment plans for neurodegenerative diseases, cardiovascular imaging and multiomics. The lecture highlighted the potential of AI algorithms to detect subtle changes at early stages through advanced multiomics techniques and medical imaging analysis. The speaker has expertise in analyzing medical images and has collaborated with medical professionals to develop AI tools for diagnosis of cancer, neurodegenerative disease, and heart disease. Why it matters: AI-driven prognosis and treatment planning promises earlier intervention and improved outcomes for challenging diseases in the region.
Professor Eran Segal presented The Human Phenotype Project, a longitudinal cohort study with over 10,000 participants. The project aims to identify molecular markers and develop prediction models for disease using deep profiling techniques including medical history, lifestyle, blood tests, and microbiome analysis. The study provides insights into drivers of obesity, diabetes, and heart disease, identifying novel markers at the microbiome, metabolite, and immune system level. Why it matters: Such large-scale phenotyping initiatives could inform personalized medicine approaches relevant to the Middle East's specific health challenges.