Teona Z. Carciumaru
Papers
1
Total Citations
14
H-Index
1
About
Dr. Teona Z. Carciumaru is a rising leader in surgical data science, whose work sits at the intersection of machine learning and minimally invasive surgery. Her research focuses on developing and validating non-optical motion tracking systems (NOMTS) to analyze surgical performance, a critical step toward objective, automated skill assessment. Her most cited work, a systematic review published in 2025, rigorously examines ML applications using NOMTS in surgery, distilling insights from over 3,600 records to map the field’s objectives, experimental designs, and model effectiveness. This foundational paper has already garnered 14 citations, signaling its rapid impact on guiding future research directions. Dr. Carciumaru’s contributions are particularly notable for bridging the gap between raw motion data and actionable surgical feedback, offering a pathway to safer, more efficient training. Her work not only advances the technical frontier of surgical analytics but also provides a clear roadmap for integrating these tools into clinical practice, making her a key voice in the next generation of surgical innovation.
Research Focus
Key Achievements
Top Papers
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