ReviewGenomics, proteomics & bioinformatics2019
Functional Neuroimaging in the New Era of Big Data.
Review in Genomics, proteomics & bioinformatics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 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
19 citing papers in PubMed.
- Towards Clinical Diagnoses: Classifying Alzheimer's Disease Using Single fMRI, Small Datasets, and Transfer Learning.Brain and behavior · 2025Article
- Reporting checklists in neuroimaging: promoting transparency, replicability, and reproducibility.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024Review
- Neuroimaging Biomarkers in Addiction.medRxiv : the preprint server for health sciences · 2024Article
- Tumor characteristics, brain functional activity, and connectivity of tinnitus in patients with vestibular schwannoma: a pilot study.Quantitative imaging in medicine and surgery · 2024Article
- Audiovisualization of real-time neuroimaging data.PloS one · 2024Article
- Events in context-The HED framework for the study of brain, experience and behavior.Frontiers in neuroinformatics · 2024Article
- Effect of transcranial direct current stimulation on postpartum depression: A study protocol for a randomized controlled trial.Frontiers in psychology · 2023Article
- Systematic bibliometric and visualized analysis of research hotspots and trends in attention-deficit hyperactivity disorder neuroimaging.Frontiers in neuroscience · 2023Article
- The evolution of Big Data in neuroscience and neurology.Journal of big data · 2023Article
- The diagnostic performance of machine learning based on resting-state functional magnetic resonance imaging data for major depressive disorders: a systematic review and meta-analysis.Frontiers in neuroscience · 2023Review
- BLMM: Parallelised computing for big linear mixed models.NeuroImage · 2022Article
- Multi-modal intermediate integrative methods in neuropsychiatric disorders: A review.Computational and structural biotechnology journal · 2022Review
- Editorial: Multi-dimensional characterization of neuropsychiatric disorders.Frontiers in neuroscience · 2022Article
- Connectivity-based Cortical Parcellation via Contrastive Learning on Spatial-Graph Convolution.BME frontiers · 2022Article
- DTFLOW: Inference and Visualization of Single-cell Pseudotime Trajectory Using Diffusion Propagation.Genomics, proteomics & bioinformatics · 2021Article
- Characterization of Brain Iron Deposition Pattern and Its Association With Genetic Risk Factor in Alzheimer's Disease Using Susceptibility-Weighted Imaging.Frontiers in human neuroscience · 2021Article
- Fisher Scoring for crossed factor linear mixed models.Statistics and computing · 2021Article
- Promoting global collaboration for brain health research.BMJ (Clinical research ed.) · 2020Article
- Big Data and the Brain: Peeking at the Future.Genomics, proteomics & bioinformatics · 2019Article
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
The field of functional neuroimaging has substantially advanced as a big data science in the past decade, thanks to international collaborative projects and community efforts. Here we conducted a literature review on functional neuroimaging, with focus on three general challenges in big data tasks: data collection and sharing, data infrastructure construction, and data analysis methods. The review covers a wide range of literature types including perspectives, database descriptions, methodology developments, and technical details. We show how each of the challenges was proposed and addressed, and how these solutions formed the three core foundations for the functional neuroimaging as a big data science and helped to build the current data-rich and data-driven community. Furthermore, based on our review of recent literature on the upcoming challenges and opportunities toward future scientific discoveries, we envisioned that the functional neuroimaging community needs to advance from the current foundations to better data integration infrastructure, methodology development toward improved learning capability, and multi-discipline translational research framework for this new era of big data.
Indexed as
Identifiers
What OpenQuestion 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 OpenQuestion graph.