2 papers
eess.IV2024
Unraveling Radiomics Complexity: Strategies for Optimal Simplicity in Predictive Modeling
Mahdi Ait Lhaj Loutfi, Teodora Boblea Podasca, Alex Zwanenburg +18
Background: The high dimensionality of radiomic feature sets, the variability in radiomic feature types and potentially high computational requirements all underscore the need for…
cs.CV2024
Pulmonary Embolism Mortality Prediction Using Multimodal Learning Based on Computed Tomography Angiography and Clinical Data
Zhusi Zhong, Helen Zhang, Fayez H. Fayad +12
Purpose: Pulmonary embolism (PE) is a significant cause of mortality in the United States. The objective of this study is to implement deep learning (DL) models using Computed Tomo…