A visual analytics approach for pattern-recognition in patient-generated data

Daniel J. Feller,Marissa Burgermaster,Matthew E. Levine,Arlene Smaldone,Patricia G. Davidson,David J. Albers,Lena Mamykina

A visual analytics approach for pattern-recognition in patient-generated data

2018

Daniel J. Feller
Marissa Burgermaster
Matthew E. Levine
Arlene Smaldone
Patricia G. Davidson
David J. Albers
Lena Mamykina

Objective To develop and test a visual analytics tool to help clinicians identify systematic and clinically meaningful patterns in patient-generated data (PGD) while decreasing perceived information overload.

Keywords:

Data mining
Information retrieval
Patient Generated Data
Visual analytics
Medicine
in patient
Hierarchical clustering
Visualization
behavioral interventions
future studies
Physical medicine and rehabilitation
Information overload
Logbook

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