Abstract
(1) Background: The Electronic Medical Record system, which is a digital medical record management architecture, is critical for reliable medical research. It facilitates the investigation of disease patterns and efficient treatment via collaboration with data scientists. (2) Methods: In this study, we present multidimensional visual tools for the analysis of multidimensional datasets via a combination of 3-dimensional radial coordinate visualization (3D RadVis) and many-objective optimization (e.g., Parallel Coordinates). Also, we propose a user-driven research design to facilitate visualization. We followed a design process to (1) understand the demands of domain experts, (2) define the problems based on relevant works, (3) design visualization, (4) implement visualization, and (5) enable qualitative evaluation by domain experts. (3) Results: This study provides clinical insight into dementia based on EMR data via visual analysis. Results of a case study based on questionnaires surveying daily living activities indicated that daily behaviors influenced the progression of dementia. (4) Conclusions: This study provides a visual analytical tool to support cluster segmentation. Using this tool, we segmented dementia patients into clusters and interpreted the behavioral patterns of each group. This study contributes to biomedical data interpretation based on a visual approach.
Highlights
The Electronic Medical Record (EMR) system has been utilized as a tool by medical experts to enhance data analysis and enable systematic control of medical records
This study has been subjected to data mining [27,28] to extract the variables that significantly affect the diagnosis of dementia
We reviewed our study to improve these limitations based on the study of Ibrahim et al [33,34], which spread the distribution of nodes evenly using Pareto front methods to 3D RadVis model
Summary
The Electronic Medical Record (EMR) system has been utilized as a tool by medical experts to enhance data analysis and enable systematic control of medical records. Medical records and diagnostic variables comprising EMR vary widely. A system that can facilitate organization of these data is imperative. The EMR analysis includes multidimensional data, because the data contain several variables. Multidimensional data analytics play an important role in understanding and analyzing EMR data
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