Population Health Methods and Tools
Under construction. More information will be posted soon. In the meantime, please browse the publications listed below to learn more about the work taking place in our lab as part of this project.
Publications
Expanding the Existing Cadence Event Sequence Visual Analysis Tool to Support the Standardized Data Model OMOP CDM
The differences in health data models obstruct the use of analytics tools on new datasets or at other institutions. This work presents …
A survey of OMOP CDM-compatible visualization tools & what the community may do to support tool development and adoption
Data visualization generates a visual representation of data that enables data exploration and data analytics to gain new information …
Local, Interactive, and Actionable: A Pandemic Behavioral Nudge
The informational environment surrounding the Covid-19 pandemic has been widely recognized as fragmented, politicized, and complex. …
Risk Prediction Tools in an Intuition-Based World: A Mixed Methods Study of Urologic Surgeons
A plethora of risk prediction tools (RPTs) have been developed to support surgical decision-making. However, past studies indicate both …
Hung-Jui Tan, Allison Deal, Antonia Bennett, Susan Blalock, Alex Sox-Harris, Daniel Reuland, Arlene Chung, David Gotz, Matthew Nielsen, Ethan Basch
September 2021
American Urological Association (AUA) Annual Meeting Abstract
Enabling Longitudinal Exploratory Analysis of Clinical COVID Data
As the COVID-19 pandemic continues to impact the world, data is being gathered and analyzed to better understand the disease. …
David Borland, Irena Brain, Karamarie Fecho, Emily Pfaff, Hao Xu, James Champion, Chris Bizon, David Gotz
August 2021
Visual Analytics in Healthcare
Interpretable Anomaly Detection in Event Sequences via Sequence Matching and Visual Comparison
Anomaly detection is a common analytical task that aims to identify rare cases that differ from the typical cases that make up the …
July 2021
IEEE TVCG (Early Access)
Selection-Bias-Corrected Visualization via Dynamic Reweighting
The collection and visual analysis of large-scale data from complex systems, such as electronic health records or clickstream data, has …
Visual Analytics to Combat Selection Bias in Retrospective EHR Data Analyses
Retrospective analyses of electronic health records (EHRs) and other health data sources are increasingly common as investigators seek …
November 2020
American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract
Selection Bias Tracking and Detailed Subset Comparison for High-Dimensional Data
The collection of large, complex datasets has become common across a wide variety of domains. Visual analytics tools increasingly play …
January 2020
IEEE TVCG (Volume 26, Issue 1)
Visual Analysis of High-Dimensional Event Sequence Data via Dynamic Hierarchical Aggregation
Temporal event data are collected across a broad range of domains, and a variety of visual analytics techniques have been developed to …
January 2020
IEEE TVCG (Volume 26, Issue 1)
Precision VISSTA: Bring-Your-Own-Device (BYOD) mHealth Data for Precision Health
A Bring-Your-Own-Device (BYOD) model for contributing mobile health (mHealth) data enables real-world data collection as patients go …
November 2019
American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract
Precision VISSTA: Machine Learning Prediction and Inference for Bring-Your-Own-Device (BYOD) mHealth Data
Precision VISSTA is a bring-your-own-device (BYOD) mobile health (mHealth) patient-powered research study focused on Inflammatory Bowel …
November 2019
American Medical Informatics Association (AMIA) Annual Symposium Podium Abstract
Dynamic Hierarchical Aggregation, Selection Bias Tracking, and Detailed Subset Comparison for High-Dimensional Event Sequence Data
With the increase in collection of temporal event data, especially electronic health record (EHR) data, numerous different …
October 2019
Visual Analytics in Healthcare (VAHC) Workshop Posters
Visual Progression Analysis of Event Sequence Data
Event sequence data is common to a broad range of application domains, from security to health care to scholarly communication. This …
January 2019
IEEE TVCG (Volume 25, Issue 1)
Visual Cohort Queries for High-Dimensional Data: A Design Study
The large collections of electronic health data gathered by modern health institutions are increasingly being leveraged as a source of …
November 2018
Visual Analytics in Healthcare (VAHC) Workshop
Clinical Concept Value Sets and Interoperability in Health Data Analytics
This paper focuses on value sets as an essential component in the health analytics ecosystem. We discuss shared repositories of …
Sigfried Gold, Andrea Batch, Robert McClure, Guoqian Jiang, Hadi Kharrazi, Rishi Saripalle, Vojtech Huser, Chunhua Weng, Nancy Roderer, Ana Szarfman, Niklas Elmqvist, David Gotz
November 2018
AMIA Annual Symposium
EventThread: Visual Summarization and Stage Analysis of Event Sequence Data
Event sequence data such as electronic health records, a person’s academic records, or car service records, are ordered series of …
January 2018
IEEE TVCG (Volume 24, Issue 1)
Adaptive Contextualization Methods for Combating Selection Bias During High-Dimensional Visualization
Large and high-dimensional real-world datasets are being gathered across a wide range of application disciplines to enable data-driven …
November 2017
ACM TiiS (Volume 7, Issue 4)
Flexible bootstrapping and analytic approaches towards the clustering of complex medical data
Identifying subgroups from a severely heterogeneous population is major challenge for Big Data. Different clustering methods optimize …
Rachael Hageman Blair, Brian Chapman, Arianna Di Florio, Ellen Eischen, David Gotz, Mathews Jacob, Han Yu
November 2016
NIH Big Data to Knowledge (BD2K) All Hands Meeting Posters
Understanding Care Plans of Community Acquired Pneumonia Based on Sankey Diagram
A care plan is a sequence of medical interventions formulated for curing a specified disease. Doctors usually craft different care …
November 2016
Visual Analytics in Healthcare (VAHC) Workshop
Adaptive Contextualization: Combating Bias During High-Dimensional Visualization and Data Selection
Large and high-dimensional real-world datasets are being gathered across a wide range of application disciplines to enable data-driven …
March 2016
ACM International Conference on Intelligent User Interfaces (IUI)
Interactive Ensemble clustering for mixed data with application to mood disorders
Mental disorders are among the most elusive conditions in medicine and defy simple models, be they biological, psychological, social, …
November 2015
NIH Big Data to Knowledge (BD2K) All Hands Meeting Posters
Visual Assessment of Cohort Divergence During Iterative Cohort Selection
Large-scale repositories of secondary-use patient data are emerging as a critical resource for both clinical and epidemiological …
Iterative Cohort Analysis and Exploration
Cohort analysis is a widely used technique for the investigation of risk factors for groups of people. It is commonly employed to gain …
Visualizing Temporal Patterns by Clustering Patients
Medical institutions and researchers frequently collect longitudinal data by conducting a series of surveys over time. Such surveys …
November 2014
Visual Analytics in Healthcare (VAHC) Workshop
DecisionFlow: Visual Analytics for High-Dimensional Temporal Event Sequence Data
Temporal event sequence data is increasingly commonplace, with applications ranging from electronic medical records to financial …
Exploring Flow, Factors, and Outcomes of Temporal Event Sequences with the Outflow Visualization
Event sequence data is common in many domains, ranging from electronic medical records (EMRs) to sports events. Moreover, such …
ICDA: A Platform for Intelligent Care Delivery Analytics
The identification of high-risk patients is a critical component in improving patient outcomes and managing costs. This paper …
Interactive Intervention Analysis
Disease progression is often complex and seemingly unpredictable. Moreover, patients often respond in dramatically different ways to …
Interactive Visual Patient Cohort Analysis
Retrospective patient cohort analysis is a widely used technique in many healthcare studies. Due to its data intensive nature, the …
Outflow: Visualizing Patient Flow by Symptoms and Outcome
Electronic Medical Record (EMR) databases contain a large amount of temporal events such as diagnosis dates for various symptoms. …