Search · four archives

Results for multiple instance learning

or ask it as a questionAsk the stacks →

ArchivesarXiv PubMed bioRxiv chemRxiv

WhenAny time Past month Past year Past 5 years

OrderMost relevant Most cited Newest

11 papers · ranked by Valyu relevance

01
PPubMed3 Feb 2015
A Novel Multiple Instance Learning Method Based on Extreme Learning Machine
Jie Wang, Liangjian Cai, Jinzhu Peng, Yuheng Jia
Since real-world data sets usually contain large instances, it is meaningful to develop efficient and effective multiple instance learning (MIL) algorithm. As a learning paradigm, MIL is different from traditional supervised learning that handles the classification of bags comprising unlabeled instances. In this paper…
91relevance
02
BbioRxiv1 Jan 2026
Adversarial erasing enhanced multiple instance learning (siMILe): Discriminative identification of oligomeric protein structures in single molecule localization microscopy
Christian Hallgrimson, Y. Lydia Li, Claire A. Shou, Ben Cardoen + 5 more
Single-molecule localization microscopy (SMLM) achieves nanoscale imaging of complex protein structures in the cell. However, the ability to capture structural variability across cell conditions (cell lines, gene expression, treatment) from 3D point cloud SMLM data remains limited. We present siMILe, a…
89relevance
03
BbioRxiv1 Jan 2025
Adversarial erasing enhanced multiple instance learning (siMILe): Discriminative identification of oligomeric protein structures in single molecule localization microscopy
Christian Hallgrimson, Y. Lydia Li, Ben Cardoen, John Lim + 4 more
Single-molecule localization microscopy (SMLM) achieves nanoscale imaging of complex protein structures in the cell. However, the ability to capture structural variability across cell conditions (cell lines, gene expression, treatment) from 3D point cloud SMLM data remains limited. We present siMILe, a novel…
89relevance
04
BbioRxiv13 Apr 2020
DeepRC: Immune repertoire classification with attention-based deep massive multiple instance learning
Michael Widrich, Bernhard Schäfl, Milena Pavlović, Geir Kjetil Sandve + 3 more
High-throughput immunosequencing allows re-constructing the immune repertoire of an individual, which is an exceptional opportunity for new immunotherapies, immunodiagnostics, and vaccine design. Such immune repertoires are shaped by past and current immune events, for example infection and disease, and thus record an…
88relevance
05
BbioRxiv8 Apr 2023
Prediction of virus-host associations using protein language models and multiple instance learning
Dan Liu, Francesca Young, David L Robertson, Ke Yuan
Predicting virus-host associations is essential to determine the specific host species that viruses interact with, and discover if new viruses infect humans and animals. Currently, the host of the majority of viruses is unknown, particularly in microbiomes. To address this challenge, we introduce EvoMIL, a deep…
87relevance
06
PPubMed30 Apr 2026
Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy
Christian Hallgrimson, Y. Lydia Li, Claire A. Shou, Ben Cardoen + 5 more
Single-molecule localization microscopy (SMLM) achieves nanoscale imaging of complex protein structures in the cell. However, the ability to capture structural variability across cell conditions (cell lines, gene expression, treatment) from 3D point cloud SMLM data remains limited. We present siMILe, a weakly…
87relevance
07
PPubMed9 Oct 2013
Drug activity prediction using multiple-instance learning via joint instance and feature selection
Zhendong Zhao, Gang Fu, Sheng Liu, Khaled M Elokely + 3 more
'Robert J Doerksen' 'Yixin Chen' 'Dawn E Wilkins'] Background In drug discovery and development, it is crucial to determine which conformers (instances) of a given molecule are responsible for its observed biological activity and at the same time to recognize the most representative subset of features (molecular…
87relevance
08
PPubMed6 Feb 2017
Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction
Yonghui Xu, Huaqing Min, Qingyao Wu, Hengjie Song + 1 more
Multi-Instance (MI) learning has been proven to be effective for the genome-wide protein function prediction problems where each training example is associated with multiple instances. Many studies in this literature attempted to find an appropriate Multi-Instance Learning (MIL) method for genome-wide protein function…
87relevance
09
BbioRxiv29 Jul 2024
Weakly supervised learning uncovers phenotypic signatures in single-cell data
Anastasia Litinetskaya, Soroor Hediyeh-zadeh, Amir Ali Moinfar, Mohammad Lotfollahi + 1 more
To deliver clinically relevant insights from large patient cohorts profiled with single-cell technologies, a key challenge is to relate sample-level and single-cell measurements. We present MultiMIL, a deep learning framework that applies attention-based multiple-instance learning for phenotype prediction and cell…
82relevance
10
PPubMed9 Jul 2024
Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science
Bita Ghasemkhani, Ozlem Varliklar, Yunus Dogan, Semih Utku + 6 more
Simple Summary This study addresses the classification task in animal science, which helps organize and analyze complex data, essential for making informed decisions. It introduces Federated Multi-Label Learning (FMLL), a novel approach combining federated learning principles with a multi-label learning technique.…
74relevance
11
PPubMed11 Sep 2014
Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System
Mert Bal, M. Fatih Amasyali, Hayri Sever, Guven Kose + 1 more
The importance of the decision support systems is increasingly supporting the decision making process in cases of uncertainty and the lack of information and they are widely used in various fields like engineering, finance, medicine, and so forth, Medical decision support systems help the healthcare personnel to select…
67relevance

Results for multiple instance learning

A Novel Multiple Instance Learning Method Based on Extreme Learning Machine

Adversarial erasing enhanced multiple instance learning (siMILe): Discriminative identification of oligomeric protein structures in single molecule localization microscopy

Adversarial erasing enhanced multiple instance learning (siMILe): Discriminative identification of oligomeric protein structures in single molecule localization microscopy

DeepRC: Immune repertoire classification with attention-based deep massive multiple instance learning

Prediction of virus-host associations using protein language models and multiple instance learning

Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy

Drug activity prediction using multiple-instance learning via joint instance and feature selection

Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction

Weakly supervised learning uncovers phenotypic signatures in single-cell data

Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science

Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System

A Novel Multiple Instance Learning Method Based on Extreme Learning Machine

Adversarial erasing enhanced multiple instance learning (siMILe): Discriminative identification of oligomeric protein structures in single molecule localization microscopy

Adversarial erasing enhanced multiple instance learning (siMILe): Discriminative identification of oligomeric protein structures in single molecule localization microscopy

DeepRC: Immune repertoire classification with attention-based deep massive multiple instance learning

Prediction of virus-host associations using protein language models and multiple instance learning

Adversarial Erasing Enhanced Multiple Instance Learning (siMILe): Discriminative Identification of Oligomeric Protein Structures in Single Molecule Localization Microscopy

Drug activity prediction using multiple-instance learning via joint instance and feature selection

Multi-Instance Metric Transfer Learning for Genome-Wide Protein Function Prediction

Weakly supervised learning uncovers phenotypic signatures in single-cell data

Federated Multi-Label Learning (FMLL): Innovative Method for Classification Tasks in Animal Science

Performance Evaluation of the Machine Learning Algorithms Used in Inference Mechanism of a Medical Decision Support System