Mohammad T. Khasawneh
Binghamton University, Helios Universitätsklinikum Wuppertal
Papers
3
Total Citations
33
H-Index
3
About
Mohammad T. Khasawneh’s research bridges manufacturing engineering and surgical robotics, with a focus on stochastic modeling, automation, and computer vision. His early work on flexible manufacturing cells introduced a Markov chain-based approach to analyze system performance under uncertainty, laying groundwork for efficient production design. More recently, he has advanced medical robotics through a systematic review and meta-analysis of robot-assisted versus conventional total knee arthroplasty, synthesizing evidence from randomized controlled trials to clarify the comparative benefits of robotic precision in orthopedic surgery. His contributions also extend to real-time surgical assistance, where he applied YOLOv8 deep learning for object segmentation in laparoscopic cholecystectomy, enhancing intraoperative decision-making. With over 30 citations across his most-cited papers, Khasawneh’s work demonstrates a trajectory from foundational manufacturing theory to translational applications in healthcare. His 2025 meta-analysis, already garnering 14 citations, underscores the growing relevance of his research in evidence-based surgical robotics. By integrating analytical modeling with cutting-edge AI, Khasawneh exemplifies how engineering principles can drive innovation in both industrial and clinical settings.
Research Focus
Key Achievements
Top Papers
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