title: Seeing the forest through the trees: uncovering phenomic complexity through interactive network visualization.
abstract: Our aim was to uncover unrecognized phenomic relationships using force-based network visualization methods, based on observed electronic medical record data. A primary phenotype was defined from actual patient profiles in the Multiparameter Intelligent Monitoring in Intensive Care II database. Network visualizations depicting primary relationships were compared to those incorporating secondary adjacencies. Interactivity was enabled through a phenotype visualization software concept: the Phenomics Advisor. Subendocardial infarction with cardiac arrest was demonstrated as a sample phenotype; there were 332 primarily adjacent diagnoses, with 5423 relationships. Primary network visualization suggested a treatment-related complication phenotype and several rare diagnoses; re-clustering by secondary relationships revealed an emergent cluster of smokers with the metabolic syndrome. Network visualization reveals phenotypic patterns that may have remained occult in pairwise correlation analysis. Visualization of complex data, potentially offered as point-of-care tools on mobile devices, may allow clinicians and researchers to quickly generate hypotheses and gain deeper understanding of patient subpopulations.
authors.affiliation: Division of Hematology/Oncology, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Jeremy L
authors.initials: JL
authors.lastname: Warner
authors.affiliation: Department of Biomedical Informatics, Vanderbilt University, Nashville, Tennessee, USA Division of General Internal Medicine, Department of Medicine, Vanderbilt University, Nashville, Tennessee, USA.
authors.forename: Joshua C
authors.initials: JC
authors.lastname: Denny
authors.affiliation: Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA.
authors.forename: David A
authors.initials: DA
authors.lastname: Kreda
authors.affiliation: Center for Biomedical Informatics, Harvard Medical School, Boston, Massachusetts, USA Children's Hospital Informatics Program at Harvard-MIT Division of Health Science, Boston, Massachusetts, USA Department of Electrical Engineering and Computer Science, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA.
authors.forename: Gil
authors.initials: G
authors.lastname: Alterovitz
mesh_terms: D001296:Audiovisual Aids; D003626:Data Display; D010363:Pattern Recognition, Automated; D014584:User-Computer Interface
keywords: Data display; Data mining; Decision making; computer-assisted; Medical informatics applications; Phenotype