ArticleBrain sciences2021
Use of Empirical Mode Decomposition in ERP Analysis to Classify Familial Risk and Diagnostic Outcomes for Autism Spectrum Disorder.
Article in Brain sciences, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 3 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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 3 syntheses or guidelines pooled it.
- Machine learning and deep learning applied to EEG and fNIRS for early autism spectrum disorder diagnosis: a systematic review.Frontiers in psychiatry · 2026Pooled it
- Presymptomatic Biological, Structural, and Functional Diagnostic Biomarkers of Autism Spectrum Disorder.Journal of neurochemistry · 2025Pooled it
- The Value of Brain Imaging and Electrophysiological Testing for Early Screening of Autism Spectrum Disorder: A Systematic Review.Frontiers in neuroscience · 2021Pooled it
- Artificial intelligence for brain disease diagnosis using electroencephalogram signals.Journal of Zhejiang University. Science. B · 2024Review
- Advances in Autism Research: Series II.Brain sciences · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Event-related potentials (ERPs) activated by faces and gaze processing are found in individuals with autism spectrum disorder (ASD) in the early stages of their development and may serve as a putative biomarker to supplement behavioral diagnosis. We present a novel approach to the classification of visual ERPs collected from 6-month-old infants using intrinsic mode functions (IMFs) derived from empirical mode decomposition (EMD). Selected features were used as inputs to two machine learning methods (support vector machines and
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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 Socratic graph.