ReviewPsychoradiology2023
Data-driven multimodal fusion: approaches and applications in psychiatric research.
Review in Psychoradiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
24 citing papers in PubMed.
- Mapping the psychosis spectrum - imaging neurosubtypes from multiscale functional network connectivity.Molecular psychiatry · 2026Article
- Cortical microarchitecture supports preadolescent functional brain network connectivity.bioRxiv : the preprint server for biology · 2026Article
- From heterogeneity to translation: data‑driven subtyping of autism in a multilevel framework.Translational psychiatry · 2026Review
- Mapping ADHD Heterogeneity and Biotypes by Topological Deviations in Morphometric Similarity Networks.JAMA psychiatry · 2026Article
- Learning heritable multimodal brain representation via contrastive learning.Research square · 2026Article
- Neurocognitive Processing of Facial Emotion Recognition in Individuals With Depression and Suicidal Ideation: An Eye-Tracking and EEG Study.Alpha psychiatry · 2026Article
- From synapse to system: mechanistic pathways of neural signaling dysfunction in psychiatric disorders.Frontiers in cell and developmental biology · 2026Review
- A linked independent component analysis framework for characterizing site-effect patterns in multi-site structural and functional MRI.Frontiers in bioinformatics · 2026Article
- Diagnostic classification of children and adolescents with high-functioning autism spectrum disorder based on brain functional network characteristics of the dense individualized and common connectivity-based cortical landmark model.Frontiers in psychiatry · 2026Article
- Parallel multilink group joint ICA (pmg-jICA): Fusion of 3D structural and 4D functional data across multiple resting fMRI networks.Network neuroscience (Cambridge, Mass.) · 2026Article
- Should the Workload of Combining Clinical Practice With Data Collection be Considered: A Survey of Physicians With Data Collection Experience.Journal of evidence-based medicine · 2025Article
- Structural-functional fingerprinting for abnormalities investigation in glioma patients.Scientific reports · 2025Article
- AI Applications in Depression Detection and Diagnosis: Bibliometric and Visual Analysis of Trends and Future Directions.JMIR mental health · 2025Article
- Clinically Relevant Patterns of Co-Fluctuating Structure and Function in Multiple Sclerosis.European journal of neurology · 2025Article
- Multi-task machine learning reveals the functional neuroanatomy fingerprint of mental processing.bioRxiv : the preprint server for biology · 2025Article
- Unraveling Hierarchical Brain Dysfunction in Major Depressive Disorder: A Multimodal Imaging and Transcriptomic Approach.Human brain mapping · 2025Article
- Progressive subcortical involvement as spinocerebellar ataxia type 3 advances.Orphanet journal of rare diseases · 2025Article
- Mapping ADHD Heterogeneity and Biotypes through Topological Deviations in Morphometric Similarity Networks.medRxiv : the preprint server for health sciences · 2025Article
- Depression diagnosis from patient interviews using multimodal machine learning.Frontiers in psychiatry · 2025Article
- Precision TMS through the integration of neuroimaging and machine learning: optimizing stimulation targets for personalized treatment.Frontiers in human neuroscience · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
Abstract
In the era of big data, where vast amounts of information are being generated and collected at an unprecedented rate, there is a pressing demand for innovative data-driven multi-modal fusion methods. These methods aim to integrate diverse neuroimaging perspectives to extract meaningful insights and attain a more comprehensive understanding of complex psychiatric disorders. However, analyzing each modality separately may only reveal partial insights or miss out on important correlations between different types of data. This is where data-driven multi-modal fusion techniques come into play. By combining information from multiple modalities in a synergistic manner, these methods enable us to uncover hidden patterns and relationships that would otherwise remain unnoticed. In this paper, we present an extensive overview of data-driven multimodal fusion approaches with or without prior information, with specific emphasis on canonical correlation analysis and independent component analysis. The applications of such fusion methods are wide-ranging and allow us to incorporate multiple factors such as genetics, environment, cognition, and treatment outcomes across various brain disorders. After summarizing the diverse neuropsychiatric magnetic resonance imaging fusion applications, we further discuss the emerging neuroimaging analyzing trends in big data, such as N-way multimodal fusion, deep learning approaches, and clinical translation. Overall, multimodal fusion emerges as an imperative approach providing valuable insights into the underlying neural basis of mental disorders, which can uncover subtle abnormalities or potential biomarkers that may benefit targeted treatments and personalized medical interventions.
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What Socratic holds
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 Socratic graph.