Weakly-Supervised Transfer Learning With Application in Precision Medicine.
,
,
,
,
,
,
,
,
,
,
,
,
IEEE Trans Autom. Sci. Eng., October, 2024
Biologically informed deep neural networks provide quantitative assessment of intratumoral heterogeneity in post treatment glioblastoma.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
npj Digit. Medicine, 2024
Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review.
CoRR, 2024
Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm.
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
,
CoRR, 2024
Knowledge-Infused Global-Local Data Fusion for Spatial Predictive Modeling in Precision Medicine.
IEEE Trans Autom. Sci. Eng., 2022
From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response.
,
,
,
,
,
,
,
,
,
,
,
PLoS Comput. Biol., 2020
A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type.
J. Digit. Imaging, 2020
Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet.
CoRR, 2020
Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth.
Proceedings of the Simulation and Synthesis in Medical Imaging, 2020
MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers.
Bioinform., 2019
Sex Differences in Predicting Fluid Intelligence of Adolescent Brain from T1-Weighted MRIs.
Proceedings of the Adolescent Brain Cognitive Development Neurocognitive Prediction, 2019
Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment.
Proceedings of the Medical Imaging 2018: Image Perception, 2018
Quantifying glioma cell growth and invasion in vitro.
Math. Comput. Model., 2008