Richard Baumgartner - researchr alias

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Viewing Publication 1 - 23 from 23

2024

3D Segmentation of Necrotic Lung Lesions in CT Images Using Self-Supervised Contrastive LearningYiqiao Liu, Sarah Halek, Randolph Crawford, Keith Persson, Michal Tomaszewski, Shubing Wang, Richard Baumgartner, Jianda Yuan, Gregory Goldmacher, Antong Chen. access, 12:32859-32869, 2024. [doi]

2023

Multi-dimension unified Swin Transformer for 3D Lesion Segmentation in Multiple Anatomical LocationsShaoyan Pan, Yiqiao Liu, Sarah Halek, Michal Tomaszewski, Shubing Wang, Richard Baumgartner, Jianda Yuan, Gregory Goldmacher, Antong Chen. isbi 2023: 1-5 [doi]

2022

Target alignment in truncated kernel ridge regressionArash A. Amini, Richard Baumgartner, Dai Feng. nips 2022: [doi]

Unsupervised Learning to Profile Measles Outbreak Risk for US CountiesBoshu Ru, Stephanie Kujawski, Amar Das, Nelson Afanador, Richard Baumgartner, Manjiri Pawaskar. amia 2022: [doi]

2020

A Deep Learning-Facilitated Radiomics Solution for the Prediction of Lung Lesion Shrinkage in Non-Small Cell Lung Cancer TrialsAntong Chen, Jennifer Saouaf, Bo Zhou, Randolph Crawford, Jianda Yuan, Junshui Ma, Richard Baumgartner, Shubing Wang, Gregory Goldmacher. isbi 2020: 678-682 [doi]

2013

Quantifying temporal correlations: A test-retest evaluation of functional connectivity in resting-state fMRIMark Fiecas, Hernando Ombao, Dan van Lunen, Richard Baumgartner, Alexandre Coimbra, Dai Feng. neuroimage, 65:231-241, 2013. [doi]

2012

2010

2008

A multilevel tabu search algorithm for the feature selection problem in biomedical dataIdowu O. Oduntan, Michel Toulouse, Richard Baumgartner, Christopher Bowman, Ray L. Somorjai, Teodor Gabriel Crainic. cma, 55(5):1019-1033, 2008. [doi]

2006

Data complexity assessment in undersampled classification of high-dimensional biomedical dataRichard Baumgartner, Ray L. Somorjai. prl, 27(12):1383-1389, 2006. [doi]

2005

2004

Control of Sparseness for Feature SelectionErinija Pranckeviciene, Richard Baumgartner, Ray L. Somorjai, Christopher Bowman. gacm 2004: 707-715 [doi]

Consensus-Based Identification of Spectral Signatures for Classification of High-Dimensional Biomedical SpectraErinija Pranckeviciene, Richard Baumgartner, Ray L. Somorjai. icpr 2004: 319-322 [doi]

A Data-Driven, Flexible Machine Learning Strategy for the Classification of Biomedical DataRajmund L. Somorjai, Murray E. Alexander, Richard Baumgartner, Stephanie Booth, Christopher Bowman, Aleksander B. Demko, Brion Dolenko, Marina Mandelzweig, Aleksander E. Nikulin, Nicolino J. Pizzi, Erinija Pranckeviciene, Arthur R. Summers, Peter Zhilkin. In Werner Dubitzky, Francisco Azuaje, editors, Artificial Intelligence Methods And Tools For Systems Biology. Volume 5 of Computational Biology, pages 67-85, Springer, 2004. [doi]

Mapping high-dimensional data onto a relative distance plane - an exact method for visualizing and characterizing high-dimensional patternsRay L. Somorjai, B. Dolenko, Aleksander B. Demko, M. Mandelzweig, A. E. Nikulin, Richard Baumgartner, Nicolino J. Pizzi. jbi, 37(5):366-379, 2004. [doi]

2003

Reducing the Overconfidence of Base Classifiers when Combining Their DecisionsSarunas Raudys, Ray L. Somorjai, Richard Baumgartner. mcs 2003: 65-73 [doi]

Class prediction and discovery using gene microarray and proteomics mass spectroscopy data: curses, caveats, cautionsRay L. Somorjai, B. Dolenko, Richard Baumgartner. bioinformatics, 19(12):1484-1491, 2003.

2002

Comparison of Two Classification Methodologies on a Real-World Biomedical ProblemRay L. Somorjai, Arunas Janeliunas, Richard Baumgartner, Sarunas Raudys. gacm 2002: 433-441 [doi]

1999

Explorative signal processing in functional MR imagingEwald Moser, Richard Baumgartner, Markus Barth, Christian Windischberger. imst, 10(2):166-176, 1999. [doi]

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