Faster cyclic loess: normalizing RNA arrays via linear models. - Karla V. Ballman; Diane E. Grill; Ann L. Oberg; Terry M. Therneau (Bioinform., 2004)

Normalization of two-channel microarray experiments: a semiparametric approach. - Jeanette E. Eckel; C. Gennings; Terry M. Therneau; L. D. Burgoon; D. R. Boverhof; Timothy R. Zacharewski (Bioinform., 2005)

Regression analysis for comparing protein samples with 16O/18O stable-isotope labeled mass spectrometry. - Jeanette E. Eckel-Passow; Ann L. Oberg; Terry M. Therneau; C. J. Mason; Douglas W. Mahoney; K. L. Johnson; J. E. Olson; H. R. Bergen III (Bioinform., 2006)

Joint estimation of calibration and expression for high-density oligonucleotide arrays. - Ann L. Oberg; Douglas W. Mahoney; Karla V. Ballman; Terry M. Therneau (Bioinform., 2006)

Quantitating tissue specificity of human genes to facilitate biomarker discovery. - George Vasmatzis; Eric W. Klee; Dagmar M. Kube; Terry M. Therneau; Farhad Kosari (Bioinform., 2007)

A fuzzy c-means algorithm using a correlation metrics and gene ontology. - Mingrui Zhang; Terry M. Therneau; Michael A. McKenzie; Peter W. Li; Ping Yang (ICPR, 2008)

Spatial normalization improves the quality of genotype calling for Affymetrix SNP 6.0 arrays. - High-Seng Chai; Terry M. Therneau; Kent R. Bailey; Jean-Pierre A. Kocher (BMC Bioinform., 2010)

A new statistic for identifying batch effects in high-throughput genomic data that uses guided principal component analysis. - Sarah E. Reese; Kellie J. Archer; Terry M. Therneau; Elizabeth J. Atkinson; Celine M. Vachon; Mariza de Andrade; Jean-Pierre A. Kocher; Jeanette E. Eckel-Passow (Bioinform., 2013)

Calculating Sample Size Estimates for RNA Sequencing Data. - Steven N. Hart; Terry M. Therneau; Yuji Zhang 001; Gregory A. Poland; Jean-Pierre A. Kocher (J. Comput. Biol., 2013)

BIMA V3: an aligner customized for mate pair library sequencing. - Travis M. Drucker; Sarah H. Johnson; Stephen J. Murphy; Kendall W. Cradic; Terry M. Therneau; George Vasmatzis (Bioinform., 2014)

Temporal Pattern and Association Discovery of Diagnosis Codes Using Deep Learning. - Saeed Mehrabi 003; Sunghwan Sohn; Dingcheng Li; Joshua J. Pankratz; Terry M. Therneau; Jennifer L. St. Sauver; Hongfang Liu; Mathew J. Palakal (ICHI, 2015)

Extending Association Rule Summarization Techniques to Assess Risk of Diabetes Mellitus. - György J. Simon; Pedro J. Caraballo; Terry M. Therneau; Steven S. Cha; M. Regina Castro; Peter W. Li (IEEE Trans. Knowl. Data Eng., 2015)

A Topic-modeling Based Framework for Drug-drug Interaction Classification from Biomedical Text. - Dingcheng Li; Sijia Liu 002; Majid Rastegar-Mojarad; Yanshan Wang; Xiaodi Li; Vipin Chaudhary; Terry M. Therneau; Hongfang Liu (AMIA, 2016)

Drug-drug Interaction Detection with A Topic-modeling Based Framework Augmented with Distant-supervision. - Dingcheng Li; Sijia Liu 002; Majid Rastegar-Mojarad; Yanshan Wang; Xiaodi Li; Vipin Chaudhary; Terry M. Therneau; Hongfang Liu (AMIA, 2016)

The Mayo Clinic Early Warning Score is superior to MEWS, and nursing pattern recognition can improve its accuracy further. - Santiago Romero-Brufau; Kim Gaines; Matthew G. Johnson; Joel Hickman; Terry M. Therneau; Jeanne Huddleston (AMIA, 2018)

Unsupervised Machine Learning for the Discovery of Latent Disease Clusters and Patient Subgroups Using Electronic Health Records. - Yanshan Wang; Yiqing Zhao; Terry M. Therneau; Elizabeth J. Atkinson; Ahmad P. Tafti; Nan Zhang; Shreyasee Amin; Andrew H. Limper; Hongfang Liu (CoRR, 2019)

Automatic extraction and assessment of lifestyle exposures for Alzheimer's disease using natural language processing. - Xin Zhou; Yanshan Wang; Sunghwan Sohn; Terry M. Therneau; Hongfang Liu; David S. Knopman (Int. J. Medical Informatics, 2019)

Unsupervised machine learning for the discovery of latent disease clusters and patient subgroups using electronic health records. - Yanshan Wang; Yiqing Zhao; Terry M. Therneau; Elizabeth J. Atkinson; Ahmad P. Tafti; Nan Zhang; Shreyasee Amin; Andrew H. Limper; Sundeep Khosla; Hongfang Liu (J. Biomed. Informatics, 2020)

Using machine learning to improve the accuracy of patient deterioration predictions: Mayo Clinic Early Warning Score (MC-EWS). - Santiago Romero-Brufau; Daniel Whitford; Matthew G. Johnson; Joel Hickman; Bruce W. Morlan; Terry M. Therneau; James M. Naessens; Jeanne M. Huddleston (J. Am. Medical Informatics Assoc., 2021)

Associations of quantitative susceptibility mapping with Alzheimer's disease clinical and imaging markers. - Petrice M. Cogswell; Heather J. Wiste; Matthew L. Senjem; Jeffrey L. Gunter; Stephen D. Weigand; Christopher G. Schwarz; Arvin Arani; Terry M. Therneau; Val J. Lowe; David S. Knopman; Hugo Botha; Jonathan Graff-Radford; et al. (NeuroImage, 2021)

Selecting software pipelines for change in flortaucipir SUVR: Balancing repeatability and group separation. - Christopher G. Schwarz; Terry M. Therneau; Stephen D. Weigand; Jeffrey L. Gunter; Val J. Lowe; Scott A. Przybelski; Matthew L. Senjem; Hugo Botha; Prashanthi Vemuri; Kejal Kantarci; Bradley F. Boeve; Jennifer L. Whitwell; et al. (NeuroImage, 2021)

Relationships between β-amyloid and tau in an elderly population: An accelerated failure time modelww. - Terry M. Therneau; David S. Knopman; Val J. Lowe; Hugo Botha; Jonathan Graff-Radford; David T. Jones; Prashanthi Vemuri; Michelle M. Mielke; Christopher G. Schwarz; Matthew L. Senjem; Jeffrey L. Gunter; Ronald C. Petersen; et al. (NeuroImage, 2021)

Response to "On the reproducibility of quantitative susceptibility mapping and its potential as a clinical biomarker: A comment on Cogswell et al. 2021". - Petrice M. Cogswell; Heather J. Wiste; Stephen D. Weigand; Terry M. Therneau; Clifford R. Jack Jr. (NeuroImage, 2022)