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  • 2019
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  • George Runger

Whole blood FPR1 mRNA expression predicts both non-small cell and small cell lung cancer

Morris, S., Vachani, A., Pass, H. I., Rom, W. N., Ryden, K., Weiss, G. J., Hogarth, D. K., Runger, G., Richards, D., Shelton, T. & Mallery, D. W., Jun 1 2018, In : International Journal of Cancer. 142, 11, p. 2355-2362 8 p.

Research output: Contribution to journalArticle

5 Scopus citations

Time series representation and similarity based on local autopatterns

Baydogan, M. G. & Runger, G., Mar 1 2016, In : Data Mining and Knowledge Discovery. 30, 2, p. 476-509 34 p.

Research output: Contribution to journalArticle

39 Scopus citations

Query-by-committee improvement with diversity and density in batch active learning

Kee, S., del Castillo, E. & Runger, G., Jul 2018, In : Information Sciences. 454-455, p. 401-418 18 p.

Research output: Contribution to journalArticle

7 Scopus citations

Projection-free kernel principal component analysis for denoising

Bui, A. T., Im, J. K., Apley, D. W. & Runger, G., Sep 10 2019, In : Neurocomputing. 357, p. 163-176 14 p.

Research output: Contribution to journalArticle

2 Scopus citations

Predictive modeling using a nationally representative database to identify patients at risk of developing microalbuminuria

Villa-Zapata, L., Warholak, T., Slack, M., Malone, D., Murcko, A., Runger, G. & Levengood, M., Feb 1 2016, In : International Urology and Nephrology. 48, 2, p. 249-256 8 p.

Research output: Contribution to journalArticle

Performance of next-generation sequencing on small tumor specimens and/or low tumor content samples using a commercially available platform

Morris, S., Subramanian, J., Gel, E., Runger, G., Thompson, E., Mallery, D. & Weiss, G., Apr 2018, In : PloS one. 13, 4, e0196556.

Research output: Contribution to journalArticle

4 Scopus citations

Multivariate bounded process adjustment schemes

Govind, N., del Castillo, E., Runger, G. & Janakiram, M., Jul 17 2016, (Accepted/In press) In : Quality Technology and Quantitative Management. p. 1-21 21 p.

Research output: Contribution to journalArticle

Monitoring temporal homogeneity in attributed network streams

Azarnoush, B., Paynabar, K., Bekki, J. & Runger, G., Jan 1 2016, In : Journal of Quality Technology. 48, 1, p. 28-43 16 p.

Research output: Contribution to journalArticle

31 Scopus citations

Interpretable regularized class association rules algorithm for classification in a categorical data space

Azmi, M., Runger, G. C. & Berrado, A., May 2019, In : Information Sciences. 483, p. 313-331 19 p.

Research output: Contribution to journalArticle

6 Scopus citations

Identifying nonlinear variation patterns with deep autoencoders

Howard, P., Apley, D. W. & Runger, G., Dec 2 2018, In : IISE Transactions. 50, 12, p. 1089-1103 15 p.

Research output: Contribution to journalArticle

Identifying and visualizing part-to-part variation with spatially dense optical dimensional metrology data

Shi, Z., Apley, D. W. & Runger, G., Jan 1 2019, In : Journal of Quality Technology. 51, 1, p. 3-20 18 p.

Research output: Contribution to journalArticle

GCRNN: Group-Constrained Convolutional Recurrent Neural Network

Lin, S. & Runger, G., Dec 7 2017, (Accepted/In press) In : IEEE Transactions on Neural Networks and Learning Systems.

Research output: Contribution to journalArticle

6 Scopus citations

EEG-based user performance prediction using random forest in a dynamic learning environment

Lujan-Moreno, G. A., Atkinson, R. & Runger, G., Jan 1 2016, Intelligent Tutoring Systems: Structure, Applications and Challenges. Nova Science Publishers, Inc., p. 105-128 24 p.

Research output: Chapter in Book/Report/Conference proceedingChapter

Distinct Variation Pattern Discovery Using Alternating Nonlinear Principal Component Analysis

Howard, P., Apley, D. W. & Runger, G., Oct 26 2016, (Accepted/In press) In : IEEE Transactions on Neural Networks and Learning Systems.

Research output: Contribution to journalArticle

1 Scopus citations

Discovering the Nature of Variation in Nonlinear Profile Data

Shi, Z., Apley, D. W. & Runger, G., Jul 2 2016, In : Technometrics. 58, 3, p. 371-382 12 p.

Research output: Contribution to journalArticle

5 Scopus citations

CRAFTER: a Tree-ensemble Clustering Algorithm for Static Datasets with Mixed Attributes and High Dimensionality

Lin, S., Azarnoush, B. & Runger, G., Feb 16 2018, (Accepted/In press) In : IEEE Transactions on Knowledge and Data Engineering.

Research output: Contribution to journalArticle

3 Scopus citations

Correction: Performance of next-generation sequencing on small tumor specimens and/or low tumor content samples using a commercially available platform(PLoS ONE (2018) 13:4 (e0196556) DOI: 10.1371/journal.pone.0196556)

Morris, S. M., Subramanian, J., Gel, E., Runger, G., Thompson, E. J., Mallery, D. W. & Weiss, G. J., Jun 2018, In : PloS one. 13, 6, e0200224.

Research output: Contribution to journalComment/debate

Automated data mining methods for identifying energy efficiency opportunities using whole-building electricity data

Howard, P., Runger, G., Reddy, T. A. & Katipamula, S., 2016, ASHRAE Transactions - ASHRAE Winter Conference. Amer. Soc. Heating, Ref. Air-Conditoning Eng. Inc., Vol. 122. p. 422-433 12 p.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Scopus citations

A data science approach for the classification of low-grade and high-grade ovarian serous carcinomas

Lin, S., Wang, C., Zarei, S., Bell, D. A., Kerr, S. E., Runger, G. & Kocher, J. P. A., Nov 27 2018, In : BMC Genomics. 19, 1, 841.

Research output: Contribution to journalArticle

Open Access
1 Scopus citations