Algorithmic fairness in computational medicine
Machine learning models are increasingly adopted for facilitating clinical decision-making.
However, recent research has shown that machine learning techniques may result in …
However, recent research has shown that machine learning techniques may result in …
A critical reflection on visualization research: Where do decision making tasks hide?
It has been widely suggested that a key goal of visualization systems is to assist decision
making, but is this true? We conduct a critical investigation on whether the activity of …
making, but is this true? We conduct a critical investigation on whether the activity of …
An empirical study of counterfactual visualization to support visual causal inference
Counterfactuals–expressing what might have been true under different circumstances–have
been widely applied in statistics and machine learning to help understand causal …
been widely applied in statistics and machine learning to help understand causal …
A framework to improve causal inferences from visualizations using counterfactual operators
Exploratory data analysis of high-dimensional datasets is a crucial task for which visual
analytics can be especially useful. However, the ad hoc nature of exploratory analysis can …
analytics can be especially useful. However, the ad hoc nature of exploratory analysis can …
Modeling and leveraging analytic focus during exploratory visual analysis
Visual analytics systems enable highly interactive exploratory data analysis. Across a range
of fields, these technologies have been successfully employed to help users learn from …
of fields, these technologies have been successfully employed to help users learn from …
A Survey on Optimization and Machine-learning-based Fair Decision Making in Healthcare
Z Chen, WJ Marrero - medRxiv, 2024 - medrxiv.org
Background. Unintended biases introduced by optimization and machine learning (ML)
models are of great interest to medical professionals. Bias in healthcare decisions can …
models are of great interest to medical professionals. Bias in healthcare decisions can …
[PDF][PDF] Countering simpsons paradox with counterfactuals
Visualizations are widely used to compare aggregate statistics between subsets of data.
However, aggregation can often obscure patterns or trends and produce misleading views …
However, aggregation can often obscure patterns or trends and produce misleading views …
Adversarial attacks on machine learning-aided visualizations
Research in ML4VIS investigates how to use machine learning (ML) techniques to generate
visualizations, and the field is rapidly growing with high societal impact. However, as with …
visualizations, and the field is rapidly growing with high societal impact. However, as with …
Q4EDA: A novel strategy for textual information retrieval based on user interactions with visual representations of time series
Knowing how to construct text-based Search Queries (SQs) for use in Search Engines (SEs)
such as Google or Wikipedia has become a fundamental skill. Though much data are …
such as Google or Wikipedia has become a fundamental skill. Though much data are …
Enabling longitudinal exploratory analysis of clinical covid data
As the COVID-19 pandemic continues to impact the world, data is being gathered and
analyzed to better understand the disease. Recognizing the potential for visual analytics …
analyzed to better understand the disease. Recognizing the potential for visual analytics …