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MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers.

, , , , , , и . Bioinform., 35 (19): 3812-3814 (2019)

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Colleen Swanson

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From cells to tissue: How cell scale heterogeneity impacts glioblastoma growth and treatment response., , , , , , , , , и 2 other автор(ы). PLoS Comput. Biol., (2020)A Deep Convolutional Neural Network for Annotation of Magnetic Resonance Imaging Sequence Type., , , , , , , , и . J. Digit. Imaging, 33 (2): 439-446 (2020)MetaMarker: a pipeline for de novo discovery of novel metagenomic biomarkers., , , , , , и . Bioinform., 35 (19): 3812-3814 (2019)Simulating magnetic resonance images based on a model of tumor growth incorporating microenvironment., , , , и . Medical Imaging: Image Perception, Observer Performance, and Technology Assessment, том 10577 из SPIE Proceedings, стр. 105771D. SPIE, (2018)Quantifying intra-tumoral genetic heterogeneity of glioblastoma toward precision medicine using MRI and a data-inclusive machine learning algorithm., , , , , , , , , и 15 other автор(ы). CoRR, (2024)Robust Automatic Whole Brain Extraction on Magnetic Resonance Imaging of Brain Tumor Patients using Dense-Vnet., , , , , , , и . CoRR, (2020)Simulated Diffusion Weighted Images Based on Model-Predicted Tumor Growth., , и . SASHIMI@MICCAI, том 12417 из Lecture Notes in Computer Science, стр. 32-40. Springer, (2020)Sex Differences in Predicting Fluid Intelligence of Adolescent Brain from T1-Weighted MRIs., , , , , , и . ABCD-NP@MICCAI, том 11791 из Lecture Notes in Computer Science, стр. 150-157. Springer, (2019)Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A review., , , , , , и . CoRR, (2024)Quantifying glioma cell growth and invasion in vitro.. Math. Comput. Model., 47 (5-6): 638-648 (2008)