Multimodal data integration using machine learning to predict the risk of clear cell renal cancer metastasis: a retrospective multicentre studyClear cell renal cell carcinomaMultimodal dataDeep learningMetastasisTo develop and validate a predictive combined model for metastasis in patients with clear cell ...
Fig. 2: Integration of multiome paired and unpaired data. a–c, UMAP representations of the latent spaces learned by MultiVI (a), Cobolt (b) and Seurat using the RNA-imputation based integration (c), for various rates of unpaired data, colored by cell modality. d, Modality enrichment (...
P. Multimodal machine learning: a survey and taxonomy. IEEE Trans. Pattern Anal. Mach. Intell. 41, 423–443 (2019). Article Google Scholar Yan, K. K., Zhao, H. & Pang, H. A comparison of graph- and kernel-based -omics data integration algorithms for classifying complex traits. BMC...
Dyslexia: the possible benefit of multimodal integration of fMRI- and EEG-data 来自 Semantic Scholar 喜欢 0 阅读量: 29 作者:C Grünling,M Ligges,R Huonker,M Klingert,H.-J. Mentzel,R Rzanny,WA Kaiser,H Witte,B Blanz 摘要: Biological research about dyslexia has been conducted using ...
Integration and representation issues in the annotation of multimodal data 来自 ResearchGate 喜欢 0 阅读量: 30 作者:P Paggio,C Navarretta 摘要: Proceedings of the NODALIDA 2009 workshopMultimodal Communication — from Human Behaviour to Computational Models.Editors: Costanza Navarretta, Patrizia Paggio...
FOUNDATIONS & RECENT TRENDS IN MULTIMODAL MACHINE LEARNING: PRINCIPLES, CHALLENGES, & OPEN QUESTIONS; Paul Pu Liang, Amir Zadeh, Louis-Philippe Morency Multimodal research in vision and language: A review of current and emerging trends; Shagun Uppal et al; Trends in Integration of Vision and Lang...
SparklesDialogue ✨Sparkles: Unlocking Chats Across Multiple Images for Multimodal Instruction-Following Models Link A machine-generated dialogue dataset tailored for word-level interleaved multi-image and text interactions to augment the conversational competence of instruction-following LLMs across multiple ...
from forums, social environments and even from part of accompanying images, so we review the present work in the succeeding three areas: fake news detection based on traditional machine learning, fake news detection based on single modal data, and fake news detection based on multimodal data. ...
Here, we present a deep probabilistic framework for the mosaic integration and knowledge transfer (MIDAS) of single-cell multimodal data. MIDAS simultaneously achieves dimensionality reduction, imputation and batch correction of mosaic data by using self-supervised modality alignment and information-...
Multimodal machine translation involves drawing information from more than one modality, based on the assumption that the additional modalities will contain useful alternative views of the input data. The most prominent tasks in this area are spoken language translation, image-guided translation, and vid...