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Found 4 papers, 1 papers with code
Petal-X: Human-Centered Visual Explanations to Improve Cardiovascular Risk Communication
Cardiovascular diseases (CVDs), the leading cause of death worldwide, can be prevented in most cases through behavioral interventions.
EXMOS: Explanatory Model Steering Through Multifaceted Explanations and Data Configurations
Explanations in interactive machine-learning systems facilitate debugging and improving prediction models.
Lessons Learned from EXMOS User Studies: A Technical Report Summarizing Key Takeaways from User Studies Conducted to Evaluate The EXMOS Platform
Our research involved a comprehensive examination of the impact of global explanations rooted in both data-centric and model-centric perspectives within systems designed to support healthcare experts in optimising machine learning models through both automated and manual data configurations.
Improving Primary Healthcare Workflow Using Extreme Summarization of Scientific Literature Based on Generative AI
The time needed to answer questions related to the content of abstracts was significantly lower in groups two and three compared to the first group using full abstracts.
