A rule-based sleep staging method operationalizing AASM scoring rules achieves 60.5% agreement with human majority-vote consensus on 50 PSG recordings while providing epoch-level explanations.
Explainable Artificial Intelligence (XAI): Concepts and Chal- lenges in Healthcare.AI, 4(3):652–666, September 2023
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A-ROM delivers competitive MedMNIST performance via pretrained ViT metric spaces, a concept dictionary, and kNN without backpropagation or fine-tuning, framed as interpretable few-shot learning under the Platonic Representation Hypothesis.
citing papers explorer
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Staging by the Book: Automatic Sleep Stage Classification Using Scoring Rules
A rule-based sleep staging method operationalizing AASM scoring rules achieves 60.5% agreement with human majority-vote consensus on 50 PSG recordings while providing epoch-level explanations.
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Toward Aristotelian Medical Representations: Backpropagation-Free Layer-wise Analysis for Interpretable Generalized Metric Learning on MedMNIST
A-ROM delivers competitive MedMNIST performance via pretrained ViT metric spaces, a concept dictionary, and kNN without backpropagation or fine-tuning, framed as interpretable few-shot learning under the Platonic Representation Hypothesis.