VisFCAC: An Interactive Family Clinical Attribute Comparison
August 24, 2022 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jake Gonzalez, Ngan V. T. Nguyen, Tommy Dang
arXiv ID
2208.11688
Category
cs.HC: Human-Computer Interaction
Citations
1
Venue
arXiv.org
Last Checked
4 months ago
Abstract
This paper presents VisFCAC, a visual analysis system that displays family structures along with clinical attribute of family members to effectively uncover patterns related to suicide deaths for submission to the BioVis 2020 Data Challenge. VisFCAC facilitates pattern tracing to offer insight on potential clinical attributes that might connect suicide deaths while also attempting to offer insight to prevent future suicides by at risk people with similar detected patterns. This paper lays out an approach to compare family members within a family structure to uncover patterns that may appear in clinical diagnosis data. This approach also compares two different families and their family structures to see whether there are patterns in suicide cases amongst clinical attributes outside family structures. Our solution implements a radial tree to display family structures with clinical attributes displayed on radial charts to provide in depth visual analysis and offer a comprehensive insight for underlying pattern discovery.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Human-Computer Interaction
R.I.P.
π»
Ghosted
R.I.P.
π»
Ghosted
Improving fairness in machine learning systems: What do industry practitioners need?
R.I.P.
π»
Ghosted
Identifying Stable Patterns over Time for Emotion Recognition from EEG
R.I.P.
π»
Ghosted
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
R.I.P.
π»
Ghosted
Deep Learning for Sensor-based Human Activity Recognition: Overview, Challenges and Opportunities
R.I.P.
π»
Ghosted
Educational data mining and learning analytics: An updated survey
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted