A5103166336- Surgical Simulation and Training
- Simulation-Based Education in Healthcare
- Cardiac, Anesthesia and Surgical Outcomes
- Human Motion and Animation
- Shoulder Injury and Treatment
- Innovations in Medical Education
- Hospital Admissions and Outcomes
- Demographic Trends and Gender Preferences
- Particle physics theoretical and experimental studies
- Edcuational Technology Systems
- Machine Learning and Data Classification
- Diversity and Career in Medicine
- Computational Physics and Python Applications
- Digital Imaging for Blood Diseases
- High-Energy Particle Collisions Research
University of Manchester
2025
University of Chicago
2024
University of Wisconsin–Madison
2018-2020
In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests Standard Model and in searches physics beyond it. Performing events with many final-state jets, such as all-hadronic decay top-antitop quark pairs, challenging. We present (HyPER), a novel architecture based on graph neural networks that uses hypergraph representation learning to build more powerful efficient representations events. HyPER used reconstruct parent from sets...
Objective: This study explores how common machine learning techniques can predict surgical maneuvers from a continuous video record of benchtop simulations. Background: Automatic computer vision recognition (suturing, tying, and transition) could expedite review objective assessment surgeries. Method: We recorded hand movements 37 clinicians performing simple running subcuticular suturing simulations, applied three (decision trees, random forests, hidden Markov models) to classify every 2 s...
This study evaluates if hand movements, tracked using digital video, can quantify in-context surgical performance. Participants of varied experience completed simple interrupted suturing and running subcuticular tasks. Marker-less motion tracking software traced the two-dimensional position a region for every video frame. Four expert observers rated 219 short clips participants performing task from 0 to 10 along following visual analog scales: fluidity motion, economy, tissue handling,...
In collider experiments, the kinematic reconstruction of heavy, short-lived particles is vital for precision tests Standard Model and in searches physics beyond it. Performing events with many final-state jets, such as all-hadronic decay topantitop quark pairs, challenging. We present HyPER, a graph neural network that uses blended graph-hypergraph representation learning to reconstruct parent from sets objects. HyPER tested on simulation shown perform favorably when compared existing...
Objective: This study creates linear and generalized additive models (GAMs) of video-recorded two-dimensional hand motion (synonymously referred to as movements or kinematics) predict expert-rated performance along a series surgical scales. Background: Surgical assessments are costly time consuming. Automatically quantifying may offload some burden coaching intervention by automatically collecting features psychomotor performance. Methods: Five experts rated anonymized video clips benchtop...