6 citations · 7 across the 3 of their papers we have counts for
4 papers
Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm
Lujia Wang, Hairong Wang, Fulvio D'Angelo +22
Glioblastoma (GBM) is one of the most aggressive and lethal human cancers. Intra-tumoral genetic heterogeneity poses a significant challenge for treatment. Biopsy is invasive, whic…
Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet
Sara Ranjbar, Kyle W. Singleton, Lee Curtin +5
Whole brain extraction, also known as skull stripping, is a process in neuroimaging in which non-brain tissue such as skull, eyeballs, skin, etc. are removed from neuroimages. Skul…
Learning Equations from Biological Data with Limited Time Samples
John T. Nardini, John H. Lagergren, Andrea Hawkins-Daarud +5
Equation learning methods present a promising tool to aid scientists in the modeling process for biological data. Previous equation learning studies have demonstrated that these me…
Sex differences in predicting fluid intelligence of adolescent brain from T1-weighted MRIs
Sara Ranjbar, Kyle W. Singleton, Lee Curtin +4
Fluid intelligence (Gf) has been defined as the ability to reason and solve previously unseen problems. Links to Gf have been found in magnetic resonance imaging (MRI) sequences su…