Attention-based multiple instance learning
PulseAugur coverage of Attention-based multiple instance learning — every cluster mentioning Attention-based multiple instance learning across labs, papers, and developer communities, ranked by signal.
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New SAGE framework offers semantic explanations for AI in pathology
Researchers have developed SAGE, a new post-hoc framework designed to provide semantic, language-grounded explanations for attention-based multiple instance learning (ABMIL) models used in computational pathology. Unlik…
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New AI method uses patient labels to train cancer registry models
Researchers have developed a novel framework using Attention-Based Multiple Instance Learning (ABMIL) to train deep learning models for cancer registry tasks without requiring individual report annotations. This method …
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Foundation models aid lung cancer growth pattern prediction with attention-based learning
Researchers have developed an attention-based multiple instance learning (ABMIL) framework to predict lung adenocarcinoma growth patterns from whole slide images. This method reduces the need for extensive annotations b…