87 citations
- Houston MethodistUS2 papers
- Rice UniversityUS2 papers
- University of HoustonUS2 papers
- Arizona State UniversityUS1 paper
- Baylor College of MedicineUS1 paper
- Baylor GeneticsUS1 paper
- Carnegie Mellon UniversityUS1 paper
- Center for Theoretical Biological PhysicsUS1 paper
- Cornell UniversityUS1 paper
- Depomed (United States)US1 paper
- Google (Switzerland)CH1 paper
- Google (United States)US1 paper
9 papers
Accelerating scientific discovery with Co-Scientist
Juraj Gottweis, Wei-Hung Weng, Alexander Daryin +48
Scientific discovery is driven by scientists generating novel hypotheses for complex problems that undergo rigorous experimental validation. To augment this process, we introduce C…
Dimensionality Reduction and Nearest Neighbors for Improving Out-of-Distribution Detection in Medical Image Segmentation
McKell Woodland, Nihil Patel, Austin Castelo +13
Clinically deployed deep learning-based segmentation models are known to fail on data outside of their training distributions. While clinicians review the segmentations, these mode…
AI-based, automated chamber volumetry from gated, non-contrast CT
Athira J Jacob, Ola Abdelkarim, Salma Zook +11
Background: Accurate chamber volumetry from gated, non-contrast cardiac CT (NCCT) scans can be useful for potential screening of heart failure. Objectives: To validate a new, fully…
Distal and non-symmetrical crack nucleation in delamination of plates via dimensionally-reduced peridynamics
Riccardo Cavuoto, Arsenio Cutolo, Kaushik Dayal +2
Exploiting the framework of peridynamics, a dimensionally-reduced plate formulation is developed that allows for the through-thickness nucleation and growth of fracture surfaces, e…
SkullEngine: A Multi-stage CNN Framework for Collaborative CBCT Image Segmentation and Landmark Detection
Qin Liu, Han Deng, Chunfeng Lian +8
We propose a multi-stage coarse-to-fine CNN-based framework, called SkullEngine, for high-resolution segmentation and large-scale landmark detection through a collaborative, integr…
Music to My Ears: Neural modularity and flexibility differ in response to real-world music stimuli
Melia E. Bonomo, Anthony K. Brandt, J. Todd Frazier +1
Music listening involves many simultaneous neural operations, including auditory processing, working memory, temporal sequencing, pitch tracking, anticipation, reward, and emotion,…