Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach.
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| Title: | Identifying dynamical persistent biomarker structures for rare events using modern integrative machine learning approach. |
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| Authors: | Dutta S; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA., Box AC; Stowers Institute for Medical Research, Kansas City, Missouri, USA., Li Y; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.; University of Kansas Cancer Center, Kansas City, Kansas, USA., Sardiu ME; Department of Biostatistics & Data Science, University of Kansas Medical Center, Kansas City, Kansas, USA.; University of Kansas Cancer Center, Kansas City, Kansas, USA.; Kansas Institute for Precision Medicine, University of Kansas Medical Center, Kansas City, Kansas, USA. |
| Source: | Proteomics [Proteomics] 2023 Nov; Vol. 23 (21-22), pp. e2200290. Date of Electronic Publication: 2023 Mar 10. |
| Publication Type: | Journal Article; Research Support, N.I.H., Extramural |
| Journal Info: | Publisher: Wiley-VCH Country of Publication: Germany NLM ID: 101092707 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1615-9861 (Electronic) Linking ISSN: 16159853 NLM ISO Abbreviation: Proteomics Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
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