Rambam Hospital Deploys AI System to Enhance Emergency Diagnoses and Save Lives
Rambam Health Care Campus in Haifa has introduced a unique artificial intelligence system named "Shaked" that has been operational for the past six months in its emergency department. This AI tool analyzes patient data in real time, offering diagnostic and treatment suggestions while identifying complex and unusual cases within seconds. According to Professor Shahar Sheli, head of Neurology at Rambam and AI lab director at the Technion, the system is the first AI integrated into critical decision-making points in emergency care. It has already reduced hospital admission times by one hour and specialist consultation times by 25 minutes, with expectations for further reductions in patient wait times.
The AI consolidates medical histories, compares cases, analyzes lab results, and prioritizes imaging tests such as CT scans for all emergency patients. It alerts physicians to patients at risk of rapid deterioration, even when initial clinical indicators seem stable. One notable case involved a young woman initially suspected of having a stroke; the system detected a recent dental procedure that suggested a severe gum infection causing facial nerve pressure, preventing unnecessary stroke protocols. Another sensitive case involved a four-month-old infant with a fractured thigh; the AI flagged a prior injury suggesting possible child abuse, prompting immediate reporting to authorities. Additionally, the system identified a life-threatening potassium deficiency in a 13-year-old boy, enabling prompt treatment.
Professor Sheli highlighted that imaging wait times, often lasting hours, pose significant risks. The AI weighs symptoms, medical background, clinical signs, and lab results to recommend imaging urgency and identify critical cases like internal bleeding or pulmonary embolism. Future enhancements include assisting with imaging report summaries. The system also features an integrated chat function allowing doctors to query patient histories efficiently, based on extensive medical databases maintained internally, avoiding reliance on external AI tools.
The AI's dynamic real-time updates improve accuracy and efficiency, reducing unnecessary tests and expediting hospital admissions. The project was made possible through collaboration among Rambam's leadership, emergency and pediatric teams, nursing staff, and the hospital's digital and IT division. Hospital director Dr. Michal Mekel emphasized Rambam's commitment to innovation and believes this technology will usher in a new era of precise, rapid medicine that supports clinicians and enhances patient care while preserving the human connection.
