( en | de | ru )

 

Disambiguation of "Kenost, Colleen"

Author of the publication

copydeleteadd this publication to your clipboard
Correction to: binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions.

, , , , , , and . BMC Bioinform., 21 (1): 495 (2020)

Please choose a person to relate this publication to

To differ between persons with the same name, the academic degree and the title of an important publication will be displayed. You can also use the button next to the name to display some publications already assigned to the person.

Colleen Kapklein

Colleen Manassa

Colleen Dockery

Colleen Swanson

Shannon Colleen Pfohman

 

Other publications of authors with the same name

Interpretation of 'Omics dynamics in a single subject using local estimates of dispersion between two transcriptomes., , , , , , , , and . AMIA, AMIA, (2019)DSL-TEACH: Data Science Literacy Training to Enhance Approaches for Clinical decision-making in Healthcare., , , , , and . AMIA, AMIA, (2019)Metrics and tools for consistent cohort discovery and financial analyses post-transition to ICD-10-CM., , , , , , , , , and . JAMIA, 22 (3): 730-737 (2015)COPD Hospitalization Risk Increased with Distinct Patterns of Multiple Systems Comorbidities Unveiled by Network Modeling., , , , , , , , , and . AMIA, AMIA, (2014)Challenges and remediation for Patient Safety Indicators in the transition to ICD-10-CM., , , , , , and . JAMIA, 22 (1): 19-28 (2015)binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions., , , , , , and . BMC Bioinform., 21 (1): 374 (2020)Correction to: binomialRF: interpretable combinatoric efficiency of random forests to identify biomarker interactions., , , , , , and . BMC Bioinform., 21 (1): 495 (2020)Systems of Phenome-Exposome Associations Unveiled by Mining Practice-Based Evidence with Environmental Exposures., , , , , and . AMIA, AMIA, (2018)Developing a 'personalome' for precision medicine: emerging methods that compute interpretable effect sizes from single-subject transcriptomes., , , , , and . Briefings Bioinform., 20 (3): 789-805 (2019)'Single-subject studies'-derived analyses unveil altered biomechanisms between very small cohorts: implications for rare diseases., , , , , , and . Bioinform., 37 (Supplement): 67-75 (2021)