Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining

Carla Floricel; Andrew Wentzel; Abdallah Mohamed; C David Fuller; Guadalupe Canahuate; G Elisabeta Marai

doi:10.1109/TVCG.2023.3326939

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Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining

Journal article

Peer reviewed

Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining

Carla Floricel, Andrew Wentzel, Abdallah Mohamed, C David Fuller, Guadalupe Canahuate and G Elisabeta Marai

IEEE transactions on visualization and computer graphics, Vol.30(1), pp.1227-1237

01/2024

DOI: 10.1109/TVCG.2023.3326939

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https://pmc.ncbi.nlm.nih.gov/articles/PMC10842255/pdf/nihms-1938449.pdfView

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Abstract

Personalized head and neck cancer therapeutics have greatly improved survival rates for patients, but are often leading to understudied long-lasting symptoms which affect quality of life. Sequential rule mining (SRM) is a promising unsupervised machine learning method for predicting longitudinal patterns in temporal data which, however, can output many repetitive patterns that are difficult to interpret without the assistance of visual analytics. We present a data-driven, human-machine analysis visual system developed in collaboration with SRM model builders in cancer symptom research, which facilitates mechanistic knowledge discovery in large scale, multivariate cohort symptom data. Our system supports multivariate predictive modeling of post-treatment symptoms based on during-treatment symptoms. It supports this goal through an SRM, clustering, and aggregation back end, and a custom front end to help develop and tune the predictive models. The system also explains the resulting predictions in the context of therapeutic decisions typical in personalized care delivery. We evaluate the resulting models and system with an interdisciplinary group of modelers and head and neck oncology researchers. The results demonstrate that our system effectively supports clinical and symptom research.

Details

Title: Subtitle: Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining
Creators: Carla Floricel - University of Illinois Chicago
Andrew Wentzel - University of Illinois Chicago
Abdallah Mohamed - The University of Texas MD Anderson Cancer Center
C David Fuller - The University of Texas MD Anderson Cancer Center
Guadalupe Canahuate - University of Iowa
G Elisabeta Marai - University of Illinois Chicago
Resource Type: Journal article
Publication Details: IEEE transactions on visualization and computer graphics, Vol.30(1), pp.1227-1237
DOI: 10.1109/TVCG.2023.3326939
eISSN: 1941-0506
Language: English
Electronic publication date: 11/28/2023
Date published: 01/2024
Academic Unit: Electrical and Computer Engineering
Record Identifier: 9984520560202771

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