Composer: Visual Cohort Analysis of Patient Outcomes
@article{Rogers2018ComposerVC, title={Composer: Visual Cohort Analysis of Patient Outcomes}, author={Jennifer Rogers and Nicholas T Spina and Ashley Neese and Rachel Hess and Darrel S. Brodke and Alexander Lex}, journal={Applied clinical informatics}, year={2018}, volume={10 2}, pages={ 278-285 } }
OBJECTIVE
Visual cohort analysis utilizing electronic health record data has become an important tool in clinical assessment of patient outcomes. [] Key Method We developed the tool in an iterative process with our collaborators to develop and refine functionality.
13 Citations
preha: Establishing Precision Rehabilitation with Visual Analytics
- Computer ScienceVCBM
- 2019
Preha is a novel visual analytics application that incorporates functionalities for data preprocessing, storage, visualization, and predictive analysis on the basis of retrospective outcomes, and it is the first integrated solution of its kind.
MedCV: An Interactive Visualization System for Patient Cohort Identification from Medical Claim Data
- MedicineProceedings of the 31st ACM International Conference on Information & Knowledge Management
- 2022
A medical claim visualization system (MedCV) that supports cohort selection from medical claim data and enables domain experts to define high-quality inclusion rules in a time-efficient manner is introduced.
Visualization Techniques of Time-Oriented Data for the Comparison of Single Patients With Multiple Patients or Cohorts: Scoping Review
- MedicineJournal of medical Internet research
- 2022
The visual comparison of measurements between single and multiple patients or cohorts is found to be underdeveloped, and is argued for further research in a systematic review, as well as the usefulness of a design space.
Sanguine: Visual analysis for patient blood management
- MedicineInf. Vis.
- 2021
Sanguine is introduced, a visual analysis tool for transfusion data and related patient medical records that was designed with two user groups in mind: PBM experts and clinicians who conduct transfusions.
Implementing an Application Programming Interface for PROMIS Measures at Three Medical Centers
- MedicineAppl. Clin. Inform.
- 2021
A software integration of an Application Programming Interface service for administering and scoring Patient-Reported Outcomes Measurement Information System (PROMIS) measures with the EHR system is created and evaluated.
A Visual Analytics Tool for Cohorts in Motion Data
- Computer ScienceVMV
- 2019
The goal is to provide a flexible system for comparative visual analytics of cohorts in motion data, which provides full flexibility in defining cohorts, selecting time intervals and spatial dimensions, and adjusting the aggregation level of summarizations.
QualDash: Adaptable Generation of Visualisation Dashboards for Healthcare Quality Improvement
- Computer Science, MedicineIEEE Transactions on Visualization and Computer Graphics
- 2021
QualDash is presented, a dashboard generation engine that allows for the dynamic configuration and deployment of visualisation dashboards for healthcare quality improvement (QI) and a metric card metaphor is defined as a unit of visual analysis in healthcare QI, leading to a Metric Specification Structure (MSS).
Coral: a web-based visual analysis tool for creating and characterizing cohorts
- BiologybioRxiv
- 2021
Coral is a web-based cohort analysis tool designed to support the analysis of genomic data from cancer patients and therefore included in the public version data from the AACR Project GENIE, The Cancer Genome Atlas, and the Cell Line Encyclopedia.
A scoping review of clinical decision support tools that generate new knowledge to support decision making in real time
- MedicineJ. Am. Medical Informatics Assoc.
- 2020
A scoping review to characterize clinical decision support systems (CDSS) that generate new knowledge to provide guidance for complex cases in real time found a number of CDSSs that generated new knowledge, although only 1 addressed confounding and bias.
THALIS: Human-Machine Analysis of Longitudinal Symptoms in Cancer Therapy
- Medicine, PsychologyIEEE Transactions on Visualization and Computer Graphics
- 2021
The approach leverages unsupervised machine learning methodology over cohorts of patients, and, in conjunction with custom visual encodings and interactions, provides context for new patients based on patients with similar diagnostic features and symptom evolution.
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