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Interactive Visual Discovery in Event Analytics: Electronic Health Records & Other Applications Ben Shneiderman Founding Director (1983-2000),

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Presentation on theme: "Interactive Visual Discovery in Event Analytics: Electronic Health Records & Other Applications Ben Shneiderman Founding Director (1983-2000),"— Presentation transcript:

1 Interactive Visual Discovery in Event Analytics: Electronic Health Records & Other Applications Ben Shneiderman ben@cs.umd.edu Founding Director (1983-2000), Human-Computer Interaction Lab Professor, Department of Computer Science Member, Institute for Advanced Computer Studies

2 Interdisciplinary research community - Computer Science & Info Studies - Psych, Socio, Educ, Jour & MITH www.cs.umd.edu/hcil vimeo.com/72440805

3 Design Issues Input devices & strategies Keyboards, pointing devices, voice Direct manipulation Menus, forms, commands Output devices & formats Screens, windows, color, sound Text, tables, graphics Instructions, messages, help Collaboration & Social Media Help, tutorials, training Search www.awl.com/DTUI Sixth Edition: 2016 Visualization

4 Information Visualization & Visual Analytics Visual bands Human percle Trend, clus.. Color, size,.. Three challe Meaningful vi Interaction: w Process mo 1999

5 Information Visualization & Visual Analytics Visual bandwidth is enormous Human perceptual skills are remarkable Trend, cluster, gap, outlier... Color, size, shape, proximity... Three challenges Meaningful visual displays of massive da Interaction: widgets & window coordinati Process models for discovery 1999 2004

6 Information Visualization & Visual Analytics Visual bandwidth is enormous Human perceptual skills are remarkable Trend, cluster, gap, outlier... Color, size, shape, proximity... Three challenges Meaningful visual displays of massive data Interaction: widgets & window coordination Process models for discovery 1999 2004 2010

7 Spotfire: Retinol’s role in embryos & vision

8 Spotfire: DC natality data

9 http://registration.spotfire.com/eval/default_edu.asp

10 10M - 100M pixels: Large displays

11 16M pixels: My New Workstation

12 100M-pixels & more

13 1M-pixels & less Small mobile devices

14 Information Visualization: Mantra Overview, zoom & filter, details-on-demand (The Eyes Have It, IEEE VL, 1996)

15 Information Visualization: Data Types 1-D Linear Document Lens, SeeSoft, Info Mural 2-D Map GIS, ArcView, PageMaker, Medical imagery 3-D World CAD, Medical, Molecules, Architecture Multi-Var Spotfire, Tableau, Qliktech, Visual Insight Temporal EventFlow, TimeSearcher, Palantir, RecordedFuture Tree Windows Explorer, SpaceTree, Treemap Network Pajek, UCINet, NodeXL, Gephi, Tom Sawyer InfoViz SciViz. flowingdata.com visualcomplexity.com eagereyes.org infosthetics.com perceptualedge.com datakind.org visual.ly visualizing.org infovis.org

16 Statistical Methods & Visual Analytics Statistical Methods Machine Learning Visual Analytics Data Algorithm Model Inspect for Errors  Clean/Filter Explore for Patterns, Find Clusters, Probe Anomalies, Split Groups, Sharpen Analytic Focus Questions, Observations, Hypotheses & Insights Comic Book Version

17 Patient ID: 45851737 12/02/2008 14:26 Arrival 12/02/2008 14:36 Emergency 12/02/2008 22:44 ICU 12/05/2008 05:07 Floor 12/14/2008 06:19 Exit Time Emergency ICU Floor Exit EHRs: Temporal data 04/26/2010 10:0031.03 04/26/2010 10:1531.01 04/26/2010 10:3031.02 04/26/2010 10:4531.08 04/26/2010 11:0031.16 Categorical Events Stock: Microsoft Numerical Events Arrival

18 Patient Histories: Our Research www.cs.umd.edu/hcil/toolname ToolEvent Types RecordsDisplay LifeLinesPoints, Intervals OneIndividual LifeLines2PointsManyIndividual, Summary SimilanPointsManyIndividual LifeFlowPointsManyIndividual, Aggregate EventFlowPoints, Intervals ManyIndividual, Aggregate

19 LifeLines: Patient Histories www.cs.umd.edu/hcil/lifelines

20 LifeLines2: Align-Rank-Filter & Summarize www.cs.umd.edu/hcil/lifelines2

21 LifeFlow: Interface with User Controls

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24 Children’s Hospital in DC: Trauma Bay

25 EventFlow Airway Breathing Circulation Disability Secondary Survey www.cs.umd.edu/hcil/eventflow

26 Children’s Hospital Trauma Care: EventFlow

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29 CDC&P: Karlyn Beer’s Giardia Study

30

31 UM-Baltimore: CHIB Projects Radiation Therapy: Metastatic Prostate Cancer Warfarin Usage in Patients with Traumatic Brain Injury

32 Yale Medical: Seth Powsner & Tami Sullivan

33 Case Studies DEVIATION, WORKFLOW: Children’s Hospital CONTRAST: Washington Hospital Center EPILEPSY: Rennes University Hospital VIOLENCE: Yale University Hospital Center ASTHMA: Army Pharmacovigilance Center DRUG: Robert H. Smith School of Business PROSTATE CANCER: Univ of Md School of Pharmacy ACTIVITY LOGS: Leidos CYBERSECURITY: Caffeine Security Consultants EMPLOYEE CAREERS: IBM Human Resources TRAFFIC INCIDENT MANAGEMENT: Baltimore Metro

34 Extraction Folding Pattern Simplification Multistep 18 Case Studies www.cs.umd.edu/hcil/eventflow

35 Recent Progress EventFlow Hierarchical Event Aggregation Sharpening Analytic Focus Simplified Overviews Event Category Matrix Workflow Management CoCo (Cohort Comparison) Taxonomy of Metrics High-Volume Hypothesis Testing

36 Future Directions: EventFlow Refine software to add business features Make backend database Scalability of many kinds Validation across usage domains Build community www.cs.umd.edu/hcil/eventflow

37 Cohort Comparison: Dual EventFlow

38 Cohort Comparison: CoCo www.cs.umd.edu/hcil/coco

39 Thanks! Catherine Plaisant LifeLines LifeLines2 (David Wang) LifeFlow (Krist Wongsuphasawat) EventFlow team (Megan Monroe, Chris Imbriano)  Sana Malik, Fan Du, etc. CoCo (Sana Malik) Sponsors: NIH, Oracle, CHIB, Adobe, Leidos

40 @benbendc EventFlow Workshop May 26, 2016 hcil.umd.edu/eventflow-workshop-2016/


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