ArticleiScience2024
Evolutionary neural architecture search for automated MDD diagnosis using multimodal MRI imaging.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Metaheuristic-optimized cross-modal attention networks for multimodal mental health assessment in college students.Frontiers in systems neuroscience · 2026Article
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Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Major depressive disorder (MDD) is a prevalent mental disorder with serious impacts on life and health. Neuroimaging offers valuable diagnostic insights. However, traditional computer-aided diagnosis methods are limited by reliance on researchers' experience. To address this, we proposed an evolutionary neural architecture search (M-ENAS) framework for automatically diagnosing MDD using multi-modal magnetic resonance imaging (MRI). M-ENAS determines the optimal weight and network architecture through a two-stage search method. Specifically, we designed a one-shot network architecture search (NAS) strategy to train supernet weights and a self-defined evolutionary search to optimize the network structure. Finally, M-ENAS was evaluated on two datasets, demonstrating that M-ENAS outperforms existing hand-designed methods. Additionally, our findings reveal that brain regions within the somatomotor network play important roles in the diagnosis of MDD, providing additional insight into the biological mechanisms underlying the disorder.
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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.