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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 40039070
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...
Algorithms Cluster Analysis Humans Machine Learning Microsatellite Instability Multiple-Instance Learning Algorithms Stomach Neoplasms
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Multiple instance learning-based prediction of programmed death-ligand 1 (PD-L1) expression from hematoxylin and eosin (H&E)-stained histopathological images in breast cancer.

PeerJ 40256728
Programmed death-ligand 1 (PD-L1) is an important biomarker increasingly used as a predictive marker in breast cancer immunotherapy. Immunohistochemical quantification remains the standard method for assessment. However, it presents challenges relate...
B7-H1 Antigen Biomarkers, Tumor Breast Neoplasms Deep Learning Eosine Yellowish-(YS) Female Hematoxylin Humans Immunohistochemistry Multiple-Instance Learning Algorithms Reproducibility of Results Staining and Labeling
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Entity-level multiple instance learning for mesoscopic histopathology images classification with Bayesian collaborative learning and pathological prior transfer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society 39921929
BACKGROUND: Entity-level pathologic structures with independent structures and functions are at a mesoscopic scale between the cell-level and slide-level, containing limited structures thus providing fewer instances for multiple instance learning. Th...
Algorithms Bayes Theorem Humans Image Interpretation, Computer-Assisted Machine Learning Multiple-Instance Learning Algorithms
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When multiple instance learning meets foundation models: Advancing histological whole slide image analysis.

Medical image analysis 39842326
Deep multiple instance learning (MIL) pipelines are the mainstream weakly supervised learning methodologies for whole slide image (WSI) classification. However, it remains unclear how these widely used approaches compare to each other, given the rece...
Deep Learning Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Multiple-Instance Learning Algorithms Neoplasm Grading Neoplasms
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The KMeansGraphMIL Model: A Weakly Supervised Multiple Instance Learning Model for Predicting Colorectal Cancer Tumor Mutational Burden.

The American journal of pathology 39800053
Colorectal cancer (CRC) is one of the top three most lethal malignancies worldwide, posing a significant threat to human health. Recently proposed immunotherapy checkpoint blockade treatments have proven effective for CRC, but their use depends on me...
Biomarkers, Tumor Colorectal Neoplasms Humans Multiple-Instance Learning Algorithms Mutation ROC Curve Supervised Machine Learning
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Colorectal cancer classification using weakly annotated whole slide images: Multiple instance learning optimization study.

Computers in biology and medicine 39798507
Colorectal cancer (CRC) is considered one of the most deadly cancer types nowadays. It is rapidly increasing due to many factors, such as unhealthy lifestyles, water and food pollution, aging, and medical diagnosis development. Detecting CRC in its e...
Algorithms Colorectal Neoplasms Deep Learning Diagnosis, Computer-Assisted Humans Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Multiple-Instance Learning Algorithms
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CAMIL: channel attention-based multiple instance learning for whole slide image classification.

Bioinformatics (Oxford, England) 39820310
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...
Algorithms Computational Biology Humans Image Processing, Computer-Assisted Machine Learning Multiple-Instance Learning Algorithms
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Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.

Cell systems 40112779
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...
Cell Shape Deep Learning Drug Discovery Humans Imaging, Three-Dimensional Melanoma Multiple-Instance Learning Algorithms
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Multiple Instance Learning-Based Prediction of Blood-Brain Barrier Opening Outcomes Induced by Focused Ultrasound.

IEEE transactions on bio-medical engineering 40030539
OBJECTIVE: Targeted blood-brain barrier (BBB) opening using focused ultrasound (FUS) and micro/nanobubbles is a promising method for brain drug delivery. This study aims to explore the feasibility of multiple instance learning (MIL) in accurate and f...
Animals Blood-Brain Barrier Contrast Media Drug Delivery Systems Machine Learning Mice Microbubbles Multiple-Instance Learning Algorithms Phospholipids Signal Processing, Computer-Assisted Sulfur Hexafluoride Ultrasonography
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Optimized multiple instance learning for brain tumor classification using weakly supervised contrastive learning.

Computers in biology and medicine 40220594
Brain tumors have a great impact on patients' quality of life and accurate histopathological classification of brain tumors is crucial for patients' prognosis. Multi-instance learning (MIL) has become the mainstream method for analyzing whole-slide i...
Algorithms Brain Neoplasms Humans Image Interpretation, Computer-Assisted Multiple-Instance Learning Algorithms Supervised Machine Learning
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