Multiple Instance Learning via Semi-supervised Laplacian TSVM
Sign Up to like & getrecommendations! Published in 2017 at "Neural Processing Letters"
DOI: 10.1007/s11063-017-9579-5
Abstract: Multiple instance learning attempts to learn from a training set consists of labeled bags each containing many unlabeled instances. In previous works, most existing algorithms mainly pay attention to the ‘most positive’ instance in each… read more here.
Keywords: instance learning; semi supervised; multiple instance; via semi ... See more keywords
Deep multiple instance selection
Sign Up to like & getrecommendations! Published in 2021 at "Science China Information Sciences"
DOI: 10.1007/s11432-020-3117-3
Abstract: Multiple instance learning (MIL) assigns a single class label to a bag of instances tailored for some real-world applications such as drug activity prediction. Classical MIL methods focus on figuring out interested instances, that is,… read more here.
Keywords: selection deep; multiple instance; selection; instance selection ... See more keywords
Multiple instance learning for sequence data with across bag dependencies
Sign Up to like & getrecommendations! Published in 2020 at "International Journal of Machine Learning and Cybernetics"
DOI: 10.1007/s13042-019-01021-5
Abstract: In Multiple Instance Learning (MIL) problem for sequence data, the instances inside the bags are sequences. In some real world applications such as bioinformatics, comparing a random couple of sequences makes no sense. In fact,… read more here.
Keywords: instance learning; multiple instance; sequence data; across bag ... See more keywords
A Multi-resolution Model for Histopathology Image Classification and Localization with Multiple Instance Learning
Sign Up to like & getrecommendations! Published in 2021 at "Computers in biology and medicine"
DOI: 10.1016/j.compbiomed.2021.104253
Abstract: Large numbers of histopathological images have been digitized into high resolution whole slide images, opening opportunities in developing computational image analysis tools to reduce pathologists' workload and potentially improve inter- and intra-observer agreement. Most previous… read more here.
Keywords: image; multiple instance; histopathology; multi resolution ... See more keywords
EpicPred: predicting phenotypes driven by epitope-binding TCRs using attention-based multiple instance learning
Sign Up to like & getrecommendations! Published in 2025 at "Bioinformatics"
DOI: 10.1093/bioinformatics/btaf080
Abstract: Abstract Motivation Correctly identifying epitope-binding T-cell receptors (TCRs) is important to both understand their underlying biological mechanism in association to some phenotype and accordingly develop T-cell mediated immunotherapy treatments. Although the importance of the CDR3… read more here.
Keywords: binding tcrs; multiple instance; epitope binding; instance learning ... See more keywords
Deep Feature Fusion Multiple Instance Learning for WaDang Recognition
Sign Up to like & getrecommendations! Published in 2019 at "IEEE Access"
DOI: 10.1109/access.2019.2929837
Abstract: WaDang recognition can provide valuable information for digital protection of cultural relics. However, WaDang recognition is challenging due to a great number of variations, such as different characters, different background pattern, and different scale and… read more here.
Keywords: multiple instance; deep feature; instance learning; recognition ... See more keywords
Deep Learning in Multiple Instance Learning: Methods, Applications, and Research Trends
Sign Up to like & getrecommendations! Published in 2025 at "IEEE Access"
DOI: 10.1109/access.2025.3625449
Abstract: Multiple instance learning (MIL) is a flexible learning framework where data is organized into sets of instances, called bags, with a single label assigned to the entire bag instead of individual instances. This formulation is… read more here.
Keywords: deep learning; learning frameworks; instance; multiple instance ... See more keywords
Leveraging Unlabelled Data in Multiple-Instance Learning Problems for Improved Detection of Parkinsonian Tremor in Free-Living Conditions
Sign Up to like & getrecommendations! Published in 2023 at "IEEE journal of biomedical and health informatics"
DOI: 10.1109/jbhi.2023.3267095
Abstract: Data-driven approaches for remote detection of Parkinson's Disease and its motor symptoms have proliferated in recent years, owing to the potential clinical benefits of early diagnosis. The holy grail of such approaches is the free-living… read more here.
Keywords: multiple instance; detection; instance learning; instance ... See more keywords
Acoustic COVID-19 Detection Using Multiple Instance Learning
Sign Up to like & getrecommendations! Published in 2024 at "IEEE Journal of Biomedical and Health Informatics"
DOI: 10.1109/jbhi.2024.3474975
Abstract: In the COVID-19 pandemic, a rigorous testing scheme was crucial. However, tests can be time-consuming and expensive. A machine learning-based diagnostic tool for audio recordings could enable widespread testing at low costs. In order to… read more here.
Keywords: detection using; acoustic covid; multiple instance; instance learning ... See more keywords
MILAMP: Multiple Instance Prediction of Amyloid Proteins
Sign Up to like & getrecommendations! Published in 2021 at "IEEE/ACM Transactions on Computational Biology and Bioinformatics"
DOI: 10.1109/tcbb.2019.2936846
Abstract: Amyloid proteins are implicated in several diseases such as Parkinson's, Alzheimer's, prion diseases, etc. In order to characterize the amyloidogenicity of a given protein, it is important to locate the amyloid forming hotspot regions within… read more here.
Keywords: instance prediction; milamp multiple; amyloid proteins; multiple instance ... See more keywords
Ensemble Learning With Attention-Based Multiple Instance Pooling for Classification of SPT
Sign Up to like & getrecommendations! Published in 2022 at "IEEE Transactions on Circuits and Systems II: Express Briefs"
DOI: 10.1109/tcsii.2021.3124165
Abstract: Tuberculosis is one of the most common infections in the human population, while reactivation of the MTB bacteria can lead to secondary pulmonary tuberculosis (SPT). SPT is a significant health risk for both immunocompromised individuals… read more here.
Keywords: attention based; spt; ensemble learning; multiple instance ... See more keywords