Zain Sayeed
Detroit Medical Center, Smith Family, Newton Wellesley Hospital
Papers
4
Total Citations
52
H-Index
3
About
Zain Sayeed is a pioneering researcher at the intersection of orthopedic surgery and artificial intelligence, with key contributions in machine learning-driven surgical prediction, robotic-assisted arthroplasty, and bionic rehabilitation. His work on volitional control of upper-limb exoskeletons using EMG sensors and machine learning (23 citations) addresses the critical challenge of processing noisy bioelectrical signals for assistive robotics, advancing human-machine interfaces for motor-impaired patients. In orthopedics, Sayeed developed machine learning models to predict blood transfusion needs after total knee arthroplasty (16 citations), identifying key risk factors to improve patient safety and reduce complications. His comparative studies on robotic versus manual knee arthroplasty (11 and 2 citations) introduced novel metrics like minimal clinically important difference (MCID) to evaluate recovery timelines, showing that robotic-assisted procedures may achieve clinically meaningful improvements faster. By bridging AI, bioengineering, and clinical outcomes, Sayeed’s work has practical implications for personalized surgical planning and postoperative care. His research portfolio, with over 50 combined citations, demonstrates a commitment to translating computational methods into tangible improvements in surgical precision, rehabilitation, and patient-reported outcomes.
Research Focus
Key Achievements
Top Papers
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