most citedBI-LAVA: Biocuration with Hierarchical Image Labeling through Active Learning and Visual Analysis

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cs.HC20241 cited

DITTO: A Visual Digital Twin for Interventions and Temporal Treatment Outcomes in Head and Neck Cancer

Andrew Wentzel, Serageldin Attia, Xinhua Zhang +3

Digital twin models are of high interest to Head and Neck Cancer (HNC) oncologists, who have to navigate a series of complex treatment decisions that weigh the efficacy of tumor co…

cs.HC2023

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

Carla Floricel, Andrew Wentzel, Abdallah Mohamed +3

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 o…

cs.HC2023

A Lens to Pandemic Stay at Home Attitudes

Andrew Wentzel, Lauren Levine, Vipul Dhariwal +5

We describe the design process and the challenges we met during a rapid multi-disciplinary pandemic project related to stay-at-home orders and social media moral frames. Unlike our…

cs.HC20231 cited

BI-LAVA: Biocuration with Hierarchical Image Labeling through Active Learning and Visual Analysis

Juan Trelles, Andrew Wentzel, William Berrios +1

In the biomedical domain, taxonomies organize the acquisition modalities of scientific images in hierarchical structures. Such taxonomies leverage large sets of correct image label…

cs.HC2023

DASS Good: Explainable Data Mining of Spatial Cohort Data

Andrew Wentzel, Carla Floricel, Guadalupe Canahuate +5

Developing applicable clinical machine learning models is a difficult task when the data includes spatial information, for example, radiation dose distributions across adjacent org…