11 citations · 14 across the 7 of their papers we have counts for
7 papers
Airway Skill Assessment with Spatiotemporal Attention Mechanisms Using Human Gaze
Jean-Paul Ainam, Rahul, Lora Cavuoto +3
Airway management skills are critical in emergency medicine and are typically assessed through subjective evaluation, often failing to gauge competency in real-world scenarios. Thi…
An Interpretable Transformer-Based Foundation Model for Cross-Procedural Skill Assessment Using Raw fNIRS Signals
A. Subedi, S. De, L. Cavuoto +3
Objective skill assessment in high-stakes procedural environments requires models that not only decode underlying cognitive and motor processes but also generalize across tasks, in…
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…
Deep Learning for Video-Based Assessment of Endotracheal Intubation Skills
Jean-Paul Ainam, Erim Yanik, Rahul Rahul +7
Endotracheal intubation (ETI) is an emergency procedure performed in civilian and combat casualty care settings to establish an airway. Objective and automated assessment of ETI sk…
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…