11 citations · 14 across the 4 of their papers we have counts for
4 papers
End-to-End Deep Learning for Real-Time Neuroimaging-Based Assessment of Bimanual Motor Skills
Aseem Subedi, Rahul, Lora Cavuoto +4
The real-time assessment of complex motor skills presents a challenge in fields such as surgical training and rehabilitation. Recent advancements in neuroimaging, particularly func…
Beyond Performance Scores: Directed Functional Connectivity as a Brain-Based Biomarker for Motor Skill Learning and Retention
Anil Kamat, Rahul Rahul, Lora Cavuoto +5
Motor skill acquisition in fields like surgery, robotics, and sports involves learning complex task sequences through extensive training. Traditional performance metrics, like exec…
Dynamic directed functional connectivity as a neural biomarker for objective motor skill assessment
Anil Kamat, Rahul Rahul, Anirban Dutta +7
Objective motor skill assessment plays a critical role in fields such as surgery, where proficiency is vital for certification and patient safety. Existing assessment methods, howe…
One-shot skill assessment in high-stakes domains with limited data via meta learning
Erim Yanik, Steven Schwaitzberg, Gene Yang +4
Deep Learning (DL) has achieved robust competency assessment in various high-stakes fields. However, the applicability of DL models is often hampered by their substantial data requ…