no code implementations • 24 Aug 2023 • Shuja Khalid, Frank Rudzicz
By using GNNs to analyze the complex visual data of surgical procedures represented as graph structures, relevant features can be extracted and surgical skill can be predicted.
no code implementations • 15 Mar 2023 • Shuja Khalid, Frank Rudzicz
We demonstrate the effectiveness of our method on a variety of static and dynamic scenes and show that it outperforms traditional SfM and MVS approaches.
no code implementations • 20 Sep 2022 • Shuja Khalid, Frank Rudzicz
We present a novel neural radiance model that is trainable in a self-supervised manner for novel-view synthesis of dynamic unstructured scenes.
no code implementations • 30 Jun 2022 • Shuja Khalid, Francisco Matos, Ayman Abunimer, Joel Bartlett, Richard Duszak, Michal Horny, Judy Gichoya, Imon Banerjee, Hari Trivedi
We developed a bi-directional Long Short Term Memory (LSTM) Network that is able to use readily available insurance data (inpatient visits, outpatient visits, and drug prescriptions) to predict 30 day re-admission for any admitted patient, regardless of reason.