AIMC Topic: Multiple-Instance Learning Algorithms

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Hierarchically Optimized Multiple Instance Learning With Multi-Magnification Pathological Images for Cerebral Tumor Diagnosis.

IEEE journal of biomedical and health informatics Jun 1, 2025
Accurate diagnosis of cerebral tumors is crucial for effective clinical therapeutics and prognosis. However, limitations in brain biopsy tissues and the scarcity of pathologists specializing in cerebral tumors hinder comprehensive clinical tests for ...
Humans Machine Learning Databases, Factual Brain Brain Neoplasms Glioma Image Interpretation, Computer-Assisted Multiple-Instance Learning Algorithms
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Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.

Cell systems Mar 19, 2025
The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and function. In this study, we used deep learning to discover morphology representations and understan...
Humans Melanoma Drug Discovery Deep Learning Imaging, Three-Dimensional Cell Shape Multiple-Instance Learning Algorithms
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CAMIL: channel attention-based multiple instance learning for whole slide image classification.

Bioinformatics (Oxford, England) Feb 4, 2025
MOTIVATION: The classification task based on whole-slide images (WSIs) is a classic problem in computational pathology. Multiple instance learning (MIL) provides a robust framework for analyzing whole slide images with slide-level labels at gigapixel...
Humans Machine Learning Algorithms Image Processing, Computer-Assisted Computational Biology Multiple-Instance Learning Algorithms
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Contrastive Pre-Training and Multiple Instance Learning for Predicting Tumor Microsatellite Instability.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2024
Accurate classification between tumor MicroSatellite Stability (MSS) and Instability (MSI) is crucial in gastrointestinal (GI) cancer prognosis and treatment. In this paper, we present a novel two-stage weakly supervised methodology, leveraging the s...
Humans Machine Learning Algorithms Stomach Neoplasms Cluster Analysis Microsatellite Instability Multiple-Instance Learning Algorithms
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