Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study
PulseAugur coverage of Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study — every cluster mentioning Multi-instance learning based artificial intelligence model to assist vocal fold leukoplakia diagnosis: A multicentre diagnostic study across labs, papers, and developer communities, ranked by signal.
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New framework improves EEG artifact removal using Multi-Instance Learning
Researchers have developed a novel framework to improve the accuracy of electroencephalography (EEG) artifact removal, specifically targeting electromyographic (EMG) contamination. This approach utilizes a frequency-awa…
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AI model predicts AML mutations from flow cytometry data
Researchers have developed an interpretable multi-instance learning model that can predict key molecular alterations in acute myeloid leukemia (AML) from routine flow cytometry data. This approach, which models patient …
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AI models lose critical cancer cues in mammography analysis · 2 papers
Two new research papers explore the degradation of crucial diagnostic information in weakly supervised AI models used for mammography. The first paper introduces a gradient-based latent decomposition method to explain w…
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New Calibratable Disambiguation Loss Improves AI Classifier Reliability
Researchers have introduced a new method called Calibratable Disambiguation Loss (CDL) to improve the reliability of classifiers in Multi-Instance Partial-Label Learning (MIPL) tasks. This plug-and-play loss function en…
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New Paper Reinterprets Image Classifiers as Multi-Instance Learners
A new paper proposes a re-evaluation of global average pooling (GAP) in image classifiers, suggesting that these models can be interpreted as multi-instance learners. The research indicates that even when an image-level…