5 papers
Scalable Identification and Prioritization of Requisition-Specific Personal Competencies Using Large Language Models
Wanxin Li, Denver McNeney, Nivedita Prabhu +5
AI-powered recruitment tools are increasingly adopted in personnel selection, yet they struggle to capture the requisition (req)-specific personal competencies (PCs) that distingui…
Multi-View Transformers for Airway-To-Lung Ratio Inference on Cardiac CT Scans: The C4R Study
Sneha N. Naik, Elsa D. Angelini, Eric A. Hoffman +4
The ratio of airway tree lumen to lung size (ALR), assessed at full inspiration on high resolution full-lung computed tomography (CT), is a major risk factor for chronic obstructiv…
Robust Quantification of Percent Emphysema on CT via Domain Attention: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study
Xuzhe Zhang, Elsa D. Angelini, Eric A. Hoffman +4
Robust quantification of pulmonary emphysema on computed tomography (CT) remains challenging for large-scale research studies that involve scans from different scanner types and fo…
Robust deep labeling of radiological emphysema subtypes using squeeze and excitation convolutional neural networks: The MESA Lung and SPIROMICS Studies
Artur Wysoczanski, Nabil Ettehadi, Soroush Arabshahi +10
Pulmonary emphysema, the progressive, irreversible loss of lung tissue, is conventionally categorized into three subtypes identifiable on pathology and on lung computed tomography…
Unsupervised Airway Tree Clustering with Deep Learning: The Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study
Sneha N. Naik, Elsa D. Angelini, R. Graham Barr +10
High-resolution full lung CT scans now enable the detailed segmentation of airway trees up to the 6th branching generation. The airway binary masks display very complex tree struct…