Discovering hierarchical common brain networks via multimodal deep belief network
Sign Up to like & getrecommendations! Published in 2019 at "Medical Image Analysis"
DOI: 10.1016/j.media.2019.03.011
Abstract: &NA; Studying a common architecture reflecting both brain's structural and functional organizations across individuals and populations in a hierarchical way has been of significant interest in the brain mapping field. Recently, deep learning models exhibited… read more here.
Keywords: network; fmri dti; multimodal deep; discovering hierarchical ... See more keywords
Long-term cancer survival prediction using multimodal deep learning
Sign Up to like & getrecommendations! Published in 2021 at "Scientific Reports"
DOI: 10.1038/s41598-021-92799-4
Abstract: The age of precision medicine demands powerful computational techniques to handle high-dimensional patient data. We present MultiSurv, a multimodal deep learning method for long-term pan-cancer survival prediction. MultiSurv uses dedicated submodels to establish feature representations… read more here.
Keywords: deep learning; multimodal deep; survival prediction; cancer ... See more keywords
Multimodal deep learning for biomedical data fusion: a review
Sign Up to like & getrecommendations! Published in 2022 at "Briefings in Bioinformatics"
DOI: 10.1093/bib/bbab569
Abstract: Abstract Biomedical data are becoming increasingly multimodal and thereby capture the underlying complex relationships among biological processes. Deep learning (DL)-based data fusion strategies are a popular approach for modeling these nonlinear relationships. Therefore, we review… read more here.
Keywords: fusion strategies; deep learning; fusion; multimodal deep ... See more keywords
Automatic Emotion Recognition Using Temporal Multimodal Deep Learning
Sign Up to like & getrecommendations! Published in 2020 at "IEEE Access"
DOI: 10.1109/access.2020.3027026
Abstract: Emotion recognition using miniaturised wearable physiological sensors has emerged as a revolutionary technology in various applications. However, detecting emotions using the fusion of multiple physiological signals remains a complex and challenging task. When fusing physiological… read more here.
Keywords: temporal multimodal; deep learning; multimodal deep; fusion ... See more keywords
A Review on Explainability in Multimodal Deep Neural Nets
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3070212
Abstract: Artificial Intelligence techniques powered by deep neural nets have achieved much success in several application domains, most significantly and notably in the Computer Vision applications and Natural Language Processing tasks. Surpassing human-level performance propelled the… read more here.
Keywords: review explainability; deep neural; explainability multimodal; neural nets ... See more keywords
Visualizing Multimodal Deep Learning for Lesion Prediction
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Computer Graphics and Applications"
DOI: 10.1109/mcg.2021.3099881
Abstract: A U-Net is a type of convolutional neural network that has been shown to output impressive results in medical imaging segmentation tasks. Still, neural networks in general form a black box that is hard to… read more here.
Keywords: visualizing multimodal; lesion prediction; learning lesion; deep learning ... See more keywords
Multimodal deep learning with feature level fusion for identification of choroidal neovascularization activity in age-related macular degeneration.
Sign Up to like & getrecommendations! Published in 2021 at "Acta ophthalmologica"
DOI: 10.1111/aos.14928
Abstract: PURPOSE This study aimed to determine the efficacy of a multimodal deep learning (DL) model using optical coherence tomography (OCT) and optical coherence tomography angiography (OCTA) images for the assessment of choroidal neovascularization (CNV) in… read more here.
Keywords: choroidal neovascularization; age; deep learning; multimodal deep ... See more keywords
DeepLPI: a multimodal deep learning method for predicting the interactions between lncRNAs and protein isoforms
Sign Up to like & getrecommendations! Published in 2021 at "BMC Bioinformatics"
DOI: 10.1186/s12859-020-03914-7
Abstract: Background Long non-coding RNAs (lncRNAs) regulate diverse biological processes via interactions with proteins. Since the experimental methods to identify these interactions are expensive and time-consuming, many computational methods have been proposed. Although these computational methods… read more here.
Keywords: protein; predicting interactions; lncrnas protein; interactions lncrnas ... See more keywords
De novo Prediction of Moonlighting Proteins Using Multimodal Deep Ensemble Learning
Sign Up to like & getrecommendations! Published in 2021 at "Frontiers in Genetics"
DOI: 10.3389/fgene.2021.630379
Abstract: Moonlighting proteins (MPs) are a special type of protein with multiple independent functions. MPs play vital roles in cellular regulation, diseases, and biological pathways. At present, very few MPs have been discovered by biological experiments.… read more here.
Keywords: novo prediction; multimodal deep; deep ensemble; ensemble learning ... See more keywords
A multistage multimodal deep learning model for disease severity assessment and early warnings of high-risk patients of COVID-19
Sign Up to like & getrecommendations! Published in 2022 at "Frontiers in Public Health"
DOI: 10.3389/fpubh.2022.982289
Abstract: The outbreak of coronavirus disease 2019 (COVID-19) has caused massive infections and large death tolls worldwide. Despite many studies on the clinical characteristics and the treatment plans of COVID-19, they rarely conduct in-depth prognostic research… read more here.
Keywords: multimodal deep; early warnings; learning; deep learning ... See more keywords