A Pretty Good Measurement classifier reformulates multi-class radiomics as quantum state discrimination and achieves competitive performance on NSCLC subtyping and PCa risk tasks.
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Hierarchy-informed curricular optimization of heterogeneous whole-brain models enables generalization to new subjects and prediction of behavioral abilities from parameters.
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Pretty Good Measurement for Radiomics: A Quantum-Inspired Multi-Class Classifier for Lung Cancer Subtyping and Prostate Cancer Risk Stratification
A Pretty Good Measurement classifier reformulates multi-class radiomics as quantum state discrimination and achieves competitive performance on NSCLC subtyping and PCa risk tasks.
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Evolution With Purpose: Hierarchy-Informed Optimization of Whole-Brain Models
Hierarchy-informed curricular optimization of heterogeneous whole-brain models enables generalization to new subjects and prediction of behavioral abilities from parameters.