@inproceedings{10714032,

title = {Medical Visual Analytics - An Interactive Approach for Analyzing Electronic Health Records},

author = {Cristian A. Secco and Lennart B. Sina and Kawa Nazemi},

doi = {10.1109/IV64223.2024.00034},

year  = {2024},

date = {2024-01-01},

urldate = {2024-01-01},

booktitle = {2024 28th International Conference Information Visualisation (IV)},

pages = {143-149},

abstract = {The evolving digitization of Germany's medical care provides new opportunities for computer-supported patient treatment. Particularly, resident medical doctors can be empowered to gather comprehensive information about the disease history, medications, and other important indicators quickly and increase the quality of treatment while maintaining the time for treatment. The central element that enables such computer-assisted support in the treatment is electronic health records (EHRs). EHRs facilitate digital access to vast medical data repositories in digital format that were previously confined to analog forms in medical facilities. However, using EHRs in daily medical treatment is time-consuming due to their unstructured textual format. There is a pressing need for analytical tools that extract the most important information from EHRs, provide that information in a quickly comprehensible way, and synthesize the entire patient history for a reliable medical treatment. In this work, we propose an innovative Visual Analytics approach and system specifically designed for medical care. Our approach and the implemented system seamlessly integrate interactive visualizations with fitting pre-trained transformer models to assist medical professionals in consolidating and presenting intricate patient data through comprehensible interactive visual interfaces. Utilizing transformer-based information extraction, it carefully manages the shift from digitized medical documents to quickly accessible patient information in a dynamic and interactive visual interface.},

keywords = {Visual analytics;Medical treatment;Data visualization;Pressing;Transformers;Information retrieval;History;Data mining;Reliability;Electronic medical records;Visual Analytics;Information Extraction;Transformer;Electronic Health Records;Decision-Support;Patient Care},

pubstate = {published},

tppubtype = {inproceedings}

}