ArticleFrontiers in genetics2019
MildInt: Deep Learning-Based Multimodal Longitudinal Data Integration Framework.
Article in Frontiers in genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 2 of them syntheses that pooled it.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
22 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- From Single-Modal to Multi-Modal Artificial Intelligence in Alzheimer's Disease: A Systematic Review of Databases, Modalities, Diagnostic Performance, and Clinical Translation Challenges.Sensors (Basel, Switzerland) · 2026Pooled it
- Deep representation learning for temporal inference in cancer omics: a systematic literature review.Briefings in bioinformatics · 2026Pooled it
- Longitudinal omics data analysis: approaches and applications.Computational and structural biotechnology journal · 2026Review
- Deep learning for Alzheimer's disease: advances in classification, segmentation, subtyping, and explainability.Biomedical engineering online · 2025Review
- Predicting prognosis of patients with hepatitis B virus-related acute-on-chronic liver failure from longitudinal ultrasound images using a multi-task deep learning approach.Annals of medicine · 2025Article
- A Smartphone-Based Non-Destructive Multimodal Deep Learning Approach Using pH-Sensitive Pitaya Peel Films for Real-Time Fish Freshness Detection.Foods (Basel, Switzerland) · 2025Article
- Article
- Explainable Machine Learning Models for Brain Diseases: Insights from a Systematic Review.Neurology international · 2024Review
- Deep learning-based approaches for multi-omics data integration and analysis.BioData mining · 2024Review
- Machine learning with multimodal neuroimaging data to classify stages of Alzheimer's disease: a systematic review and meta-analysis.Cognitive neurodynamics · 2024Review
- HANSynergy: Heterogeneous Graph Attention Network for Drug Synergy Prediction.Journal of chemical information and modeling · 2024Article
- DeepIDA-GRU: a deep learning pipeline for integrative discriminant analysis of cross-sectional and longitudinal multiview data with applications to inflammatory bowel disease classification.Briefings in bioinformatics · 2024Article
- Harnessing multimodal data integration to advance precision oncology.Nature reviews. Cancer · 2022Review
- Non-small-cell lung cancer classification via RNA-Seq and histology imaging probability fusion.BMC bioinformatics · 2021Article
- Bayesian metamodeling of complex biological systems across varying representations.Proceedings of the National Academy of Sciences of the United States of America · 2021Article
- Machine learning for modeling the progression of Alzheimer disease dementia using clinical data: a systematic literature review.JAMIA open · 2021Review
- Predicting treatment response from longitudinal images using multi-task deep learning.Nature communications · 2021Article
- DL4Burn: Burn Surgical Candidacy Prediction using Multimodal Deep Learning.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2021Article
- Toward a Multimodal Computer-Aided Diagnostic Tool for Alzheimer's Disease Conversion.Frontiers in neuroscience · 2021Article
- Intelligent Health Care: Applications of Deep Learning in Computational Medicine.Frontiers in genetics · 2021Review
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
As large amounts of heterogeneous biomedical data become available, numerous methods for integrating such datasets have been developed to extract complementary knowledge from multiple domains of sources. Recently, a deep learning approach has shown promising results in a variety of research areas. However, applying the deep learning approach requires expertise for constructing a deep architecture that can take multimodal longitudinal data. Thus, in this paper, a deep learning-based python package for data integration is developed. The python package deep learning-based
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.