Abstract
Determining infections and sepsis of severely burned adults in a timely fashion allows clinicians to provide necessary treatments to critically ill patients, potentially reducing the chance of mortality. In current practice, clinicians examine large amounts of heterogeneous medical records using a spreadsheet-like representation and perform analysis of descriptive statistics to aid in their decision making for sepsis diagnosis. A more efficient approach is required to streamline such a process; accordingly, we developed an interactive visual interface for supporting quick inspection and comparison of patients' retrospective clinical trajectories. In particular, we employ a timeline representation to present entire treatment contexts for individual patients, and an aggregated matrix representation for summarizing multiple data variables of individual patients over time. This provides clinicians with a compact and intuitive way to discover the important trends, patterns, and events that occur in the context of multiple patients. We present several possible use cases identified by clinicians using our system and show that our preliminary results have the potential to greatly improve diagnostic timing and accuracy of sepsis identification in critically ill patients.
| Original language | English (US) |
|---|---|
| Title of host publication | 2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 31-38 |
| Number of pages | 8 |
| ISBN (Electronic) | 9781538631874 |
| DOIs | |
| State | Published - Jun 15 2018 |
| Event | 8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 - Phoenix, United States Duration: Oct 1 2017 → … |
Other
| Other | 8th Annual IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017 |
|---|---|
| Country | United States |
| City | Phoenix |
| Period | 10/1/17 → … |
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ASJC Scopus subject areas
- Computer Graphics and Computer-Aided Design
- Information Systems and Management
- Media Technology
- Medicine (miscellaneous)
- Health Informatics
Cite this
Aiding infection analysis and diagnosis through temporally-contextualized matrix representations. / Gomov, Maksim; Chou, Jia Kai; Li, Jianping Kelvin; Sen, Soman; Cho, Kiho; Tran, Nam; Ma, Kwan-Liu.
2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017. Institute of Electrical and Electronics Engineers Inc., 2018. p. 31-38.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Aiding infection analysis and diagnosis through temporally-contextualized matrix representations
AU - Gomov, Maksim
AU - Chou, Jia Kai
AU - Li, Jianping Kelvin
AU - Sen, Soman
AU - Cho, Kiho
AU - Tran, Nam
AU - Ma, Kwan-Liu
PY - 2018/6/15
Y1 - 2018/6/15
N2 - Determining infections and sepsis of severely burned adults in a timely fashion allows clinicians to provide necessary treatments to critically ill patients, potentially reducing the chance of mortality. In current practice, clinicians examine large amounts of heterogeneous medical records using a spreadsheet-like representation and perform analysis of descriptive statistics to aid in their decision making for sepsis diagnosis. A more efficient approach is required to streamline such a process; accordingly, we developed an interactive visual interface for supporting quick inspection and comparison of patients' retrospective clinical trajectories. In particular, we employ a timeline representation to present entire treatment contexts for individual patients, and an aggregated matrix representation for summarizing multiple data variables of individual patients over time. This provides clinicians with a compact and intuitive way to discover the important trends, patterns, and events that occur in the context of multiple patients. We present several possible use cases identified by clinicians using our system and show that our preliminary results have the potential to greatly improve diagnostic timing and accuracy of sepsis identification in critically ill patients.
AB - Determining infections and sepsis of severely burned adults in a timely fashion allows clinicians to provide necessary treatments to critically ill patients, potentially reducing the chance of mortality. In current practice, clinicians examine large amounts of heterogeneous medical records using a spreadsheet-like representation and perform analysis of descriptive statistics to aid in their decision making for sepsis diagnosis. A more efficient approach is required to streamline such a process; accordingly, we developed an interactive visual interface for supporting quick inspection and comparison of patients' retrospective clinical trajectories. In particular, we employ a timeline representation to present entire treatment contexts for individual patients, and an aggregated matrix representation for summarizing multiple data variables of individual patients over time. This provides clinicians with a compact and intuitive way to discover the important trends, patterns, and events that occur in the context of multiple patients. We present several possible use cases identified by clinicians using our system and show that our preliminary results have the potential to greatly improve diagnostic timing and accuracy of sepsis identification in critically ill patients.
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U2 - 10.1109/VAHC.2017.8387498
DO - 10.1109/VAHC.2017.8387498
M3 - Conference contribution
AN - SCOPUS:85050149109
SP - 31
EP - 38
BT - 2017 IEEE Workshop on Visual Analytics in Healthcare, VAHC 2017
PB - Institute of Electrical and Electronics Engineers Inc.
ER -