Shapley Additive Explanations
PulseAugur coverage of Shapley Additive Explanations — every cluster mentioning Shapley Additive Explanations across labs, papers, and developer communities, ranked by signal.
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Machine learning predicts heart disease from CT scans
Researchers have developed a machine learning framework to predict obstructive coronary artery disease (CAD) using CT scans. The model analyzes features from coronary calcium and epicardial fat, identifying 14 key predi…
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AI predicts heart ischemia from CT scans using novel calcium features
Researchers have developed a new machine learning framework to predict myocardial ischemia using standard non-contrast CT calcium scoring scans. The model incorporates the Agatston score, eight novel "calcium-omics" fea…
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New FAMeX algorithm improves AI explainability over SHAP and PFI
Researchers have introduced FAMeX, a novel algorithm designed to enhance the explainability of artificial intelligence systems. This new technique utilizes a graph-theoretic approach called a Feature Association Map (FA…
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Football ML interpretations fail to transfer from elite to university leagues
A new study published on arXiv explores the transferability of machine learning interpretations in football performance analysis. Researchers found that performance determinants learned from elite European leagues did n…
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GeoAI flood mapping research aligns model explanations with domain knowledge
A new framework called ADAGE has been developed to evaluate how well explanations from Geospatial Artificial Intelligence (GeoAI) models align with established domain knowledge in satellite-based flood mapping. This fra…
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New framework enhances AI explainability for spectral data analysis
Researchers have developed the Spectral Model eXplainer (SMX), a new framework designed to improve the explainability of machine learning models used in chemometrics and spectroscopy. Unlike existing methods that focus …