Seuraa
Maciej A. Mazurowski
Maciej A. Mazurowski
Associate Professor of Biostatistics & Bioinformatics, Radiology, Comp. Sci., ECE, Duke University
Vahvistettu sähköpostiosoite verkkotunnuksessa duke.edu - Kotisivu
Nimike
Viittaukset
Viittaukset
Vuosi
A systematic study of the class imbalance problem in convolutional neural networks
M Buda, A Maki, MA Mazurowski
Neural Networks 106, 249-259, 2018
29442018
Training neural network classifiers for medical decision making: The effects of imbalanced datasets on classification performance
MA Mazurowski, PA Habas, JM Zurada, JY Lo, JA Baker, GD Tourassi
Neural Networks 21 (2-3), 427-436, 2008
10892008
Deep learning in radiology: An overview of the concepts and a survey of the state of the art with focus on MRI
MA Mazurowski, M Buda, A Saha, MR Bashir
Journal of Magnetic Resonance Imaging 49 (4), 939-954, 2019
6192019
Segment anything model for medical image analysis: an experimental study
MA Mazurowski, H Dong, H Gu, J Yang, N Konz, Y Zhang
Medical Image Analysis 89, 102918, 2023
4832023
Association of genomic subtypes of lower-grade gliomas with shape features automatically extracted by a deep learning algorithm
M Buda, A Saha, MA Mazurowski
Computers in biology and medicine 109, 218-225, 2019
3362019
Radiogenomics: What It Is and Why It Is Important
MA Mazurowski
Journal of the American College of Radiology 12 (8), 862-866, 2015
3172015
A machine learning approach to radiogenomics of breast cancer: a study of 922 subjects and 529 DCE-MRI features
A Saha, MR Harowicz, LJ Grimm, CE Kim, SV Ghate, R Walsh, ...
British journal of cancer 119 (4), 508-516, 2018
2642018
Deep learning for segmentation of brain tumors: Impact of cross‐institutional training and testing
EA AlBadawy, A Saha, MA Mazurowski
Medical physics 45 (3), 1150-1158, 2018
2642018
Radiogenomic Analysis of Breast Cancer: Luminal B Molecular Subtype Is Associated with Enhancement Dynamics at MR Imaging
MA Mazurowski, J Zhang, LJ Grimm, SC Yoon, JI Silber
Radiology 273 (2), 365-372, 2014
2632014
Management of thyroid nodules seen on US images: deep learning may match performance of radiologists
M Buda, B Wildman-Tobriner, JK Hoang, D Thayer, FN Tessler, ...
Radiology 292 (3), 695-701, 2019
1952019
Multivariate machine learning models for prediction of pathologic response to neoadjuvant therapy in breast cancer using MRI features: a study using an independent validation set
EH Cain, A Saha, MR Harowicz, JR Marks, PK Marcom, MA Mazurowski
Breast cancer research and treatment 173, 455-463, 2019
1942019
Hierarchical convolutional neural networks for segmentation of breast tumors in mri with application to radiogenomics
J Zhang, A Saha, Z Zhu, MA Mazurowski
IEEE transactions on medical imaging 38 (2), 435-447, 2019
1832019
Deep Learning for identifying radiogenomic associations in breast cancer
Z Zhu, E Albadawy, A Saha, J Zhang, MR Harowicz, MA Mazurowski
Computers in biology and medicine 109, 85-90, 2019
1632019
Computational approach to radiogenomics of breast cancer: luminal A and luminal B molecular subtypes are associated with imaging features on routine breast MRI extracted using …
LJ Grimm, J Zhang, MA Mazurowski
Journal of Magnetic Resonance Imaging 42 (4), 902-907, 2015
1592015
Radiogenomics of lower-grade glioma: algorithmically-assessed tumor shape is associated with tumor genomic subtypes and patient outcomes in a multi-institutional study with The …
MA Mazurowski, K Clark, NM Czarnek, P Shamsesfandabadi, KB Peters, ...
Journal of neuro-oncology 133, 27-35, 2017
1422017
Using artificial intelligence to revise ACR TI-RADS risk stratification of thyroid nodules: diagnostic accuracy and utility
B Wildman-Tobriner, M Buda, JK Hoang, WD Middleton, D Thayer, ...
Radiology 292 (1), 112-119, 2019
1312019
Imaging descriptors improve the predictive power of survival models for glioblastoma patients
MA Mazurowski, A Desjardins, JM Malof
Neuro-oncology 15 (10), 1389-1394, 2013
1252013
A Data Set and Deep Learning Algorithm for the Detection of Masses and Architectural Distortions in Digital Breast Tomosynthesis Images
M Buda, A Saha, R Walsh, S Ghate, N Li, A Święcicki, JY Lo, ...
JAMA network open 4 (8), e2119100-e2119100, 2021
108*2021
Artificial intelligence may cause a significant disruption to the radiology workforce
MA Mazurowski
Journal of the American College of Radiology 16 (8), 1077-1082, 2019
962019
Deep learning-based algorithm for assessment of knee osteoarthritis severity in radiographs matches performance of radiologists
A Swiecicki, N Li, J O'Donnell, N Said, J Yang, RC Mather, WA Jiranek, ...
Computers in biology and medicine 133, 104334, 2021
842021
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Artikkelit 1–20