UAE universities, including Khalifa University and Gulf Medical University, are actively leveraging AI tools for cancer research and early detection efforts. Researchers at Khalifa University are developing AI models to enhance early diagnosis and predict treatment responses across various cancers like breast, brain, lung, and prostate. Gulf Medical University also employs AI and machine learning in its research initiatives related to cancer treatment and diagnosis. Why it matters: These initiatives highlight the UAE's commitment to advancing healthcare through artificial intelligence, contributing to global efforts in disease combat and aligning with broader health equity goals.
Forbes Middle East's 30 Under 30 list for 2025 includes four KAUST students/alumni in Science and Technology, and two Saudi founders from KAUST's TAQADAM accelerator in Commerce and Finance. The KAUST honorees are Aljawharah Alsharif (wearable health tech), Arwa Alghuneim (blood cancer research), and Esraa Fakeih (femtech startup Gees). These individuals are recognized for leveraging their KAUST education and research to make real-world impacts, particularly in global health. Why it matters: This recognition highlights KAUST's role in developing Saudi talent and contributing to advancements in science, technology, and entrepreneurship within the region.
KAUST researchers developed a statistical approach to improve the identification of cancer-related protein mutations by reducing false positives. The method uses Bayesian statistics to analyze protein domain data from tumor samples, accounting for potential errors due to limited data. The team tested their method on prostate cancer data, successfully identifying a known cancer-linked mutation in the DNA binding protein cd00083. Why it matters: This enhances the reliability of cancer research at the molecular level, potentially accelerating the discovery of new therapeutic targets.
KAUST and King Abdulaziz University (KAU) have signed a memorandum of understanding (MoU) to collaborate and fund scientific research. The collaboration will focus on areas including cancer research, energy harvesting and storage, solar technology, renewable energy, and desert agriculture. The MoU was signed by Donal Bradley, KAUST VP for Research, and Yusuf Al Turki, KAU VP for Graduate Studies and Scientific Research. Why it matters: This partnership between two leading Saudi universities will help advance research and development in areas critical to Saudi Vision 2030.
MBZUAI alumnus Numan Saeed is applying machine learning to medical imaging and cancer research as a research scientist at the University. He collaborates with UAE hospitals like Sheikh Shakhbout Medical City and Cleveland Clinic to build datasets and gather clinical feedback. Saeed's team is developing a model focused on head and neck cancer using the HECKTOR dataset and local data. Why it matters: This research contributes to the UAE's healthcare ambitions by enabling earlier diagnosis and personalized care through AI-driven analysis of medical images.
Petar Stojanov from the Broad Institute of MIT and Harvard will give a talk on cancer data analysis, covering the fundamentals of cancer, the nature of large-scale data collected, and main analysis objectives. The talk will also address open questions in cancer data analysis and how machine learning and generative modeling can help. Stojanov's research focuses on applying machine learning to genomic analysis of cancer mutation and single-cell RNA sequencing data. Why it matters: Applying AI and machine learning to cancer research can lead to a better understanding of the disease and development of new therapies.
MBZUAI master's student Sayed Hashim is applying machine learning to improve cancer diagnosis and treatment, motivated by personal loss. He and fellow student Muhammad Ali developed algorithms for cancer type classification from multi-omics data, achieving over 96% accuracy. Their work, supervised by MBZUAI faculty, resulted in a published paper on multi-omics data representation learning. Why it matters: This research demonstrates the potential of AI and machine learning to advance cancer research and personalized medicine in the region.
KAUST held a "Run for a Cure" charity race on October 28 for breast cancer research, with over 425 participants from KAUST and partner organizations. A KAUST Ph.D. student discussed her research on non-invasive early cancer detection using plasma blood samples. The event included 10K, 5K, and 3K runs through KAUST, aligning with Vision 2030's goal of increasing public participation in sports. Why it matters: This event highlights KAUST's commitment to healthcare research, community engagement, and supporting national goals for health and sustainability.