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Recently, Beijing United Family Hospital has officially established a strategic partnership with Alibaba DAMO Academy, aiming to jointly promote "Innovation in AI-Driven Disease Prevention and the Economic Value of Healthcare." This collaboration will leverage DAMO Academy's "Scan and Detect Multiple Conditions" medical AI technology, combined with Beijing United Family Hospital's international medical standards and multi-location coverage advantages, to explore and implement AI-based screening services for multiple diseases that are accessible to a broad population.
Dr. Pan Zhongying, President of Beijing United Family Hospital, stated that this collaboration integrates artificial intelligence with medical care, aiming to move the management of cancer and chronic disease health forward through cutting-edge AI screening technology, providing patients with more efficient, reliable, and patient-centered healthcare services.
Focusing on Gastrointestinal Cancer and Chronic Disease Screening
One of the key focuses of this collaboration is promoting gastrointestinal cancer and chronic disease screening based on "Plain CT + AI."
Gastrointestinal Cancer Screening: This year, Beijing United Family Hospital has newly established a Gastrointestinal Cancer Center, committed to accelerating the application of advanced technologies. DAMO Academy's "Scan and Detect Multiple Conditions" technology has achieved significant results internationally, capable of identifying multiple diseases that are difficult to detect with traditional methods through a single plain CT scan, and has made breakthroughs in the screening of digestive cancers such as pancreatic cancer and gastric cancer. Related research findings have been published twice in "Nature Medicine" and have received the "Breakthrough Device" designation from the U.S. FDA.
Chronic Disease Monitoring: To address challenges such as an aging population and the high prevalence of chronic diseases, the two parties will also jointly use the "Plain CT + AI" technology to monitor chronic diseases such as osteoporosis, severe fatty liver, and cardiovascular diseases, as well as related risk factors. Notably, this technology has the potential to help identify osteoporosis risks in populations other than postmenopausal women, thereby providing more accurate and personalized lifelong health management services.
This collaboration will fully leverage the technical and service strengths of both sides, exploring the application of AI throughout the entire medical service process, offering new directions for the innovation of disease prevention and health management models.
