ArticleIEEE transactions on medical imaging2021
Deep Relational Reasoning for the Prediction of Language Impairment and Postoperative Seizure Outcome Using Preoperative DWI Connectome Data of Children With Focal Epilepsy.
Article in IEEE transactions on medical imaging, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers, 1 of them a synthesis that pooled it.
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Who cites it
13 citing papers in PubMed, 1 synthesis or guideline pooled it, 21 citations in OpenAlex.
- Artificial intelligence role in advancement of human brain connectome studies.Frontiers in neuroinformatics · 2024Pooled it
- AI enabled decision support systems in epilepsy surgery a scoping review.Research square · 2026Article
- Diffusion Tractography Biomarker for Epilepsy Severity in Children With Drug-Resistant Epilepsy.Annals of clinical and translational neurology · 2026Article
- Deep learning enabled decision support systems in epilepsy surgery: a scoping review.npj health systems · 2026Article
- Enhancing Developmental Language Disorder Identification with Artificial Intelligence: Development of an Explainable Screening App Using Real and Synthetic Data.Journal of autism and developmental disorders · 2025Article
- Volumetric Medical Image Segmentation Through Dual Self-Distillation in U-Shaped Networks.IEEE transactions on bio-medical engineering · 2025Article
- Deep Learning-Based Tract Classification of Preoperative DWI Tractography Advances the Prediction of Short-Term Postoperative Language Improvement in Children With Drug-Resistant Epilepsy.IEEE transactions on bio-medical engineering · 2025Article
- Decreased GABA levels during development result in increased connectivity in the larval zebrafish tectum.bioRxiv : the preprint server for biology · 2024Article
- Recognizing Pediatric Tuberous Sclerosis Complex Based on Multi-Contrast MRI and Deep Weighted Fusion Network.Bioengineering (Basel, Switzerland) · 2023Article
- Spatial-Temporal Synchronous Graph Transformer network (STSGT) for COVID-19 forecasting.Smart health (Amsterdam, Netherlands) · 2022Article
- Review
- Deep reasoning neural network analysis to predict language deficits from psychometry-driven DWI connectome of young children with persistent language concerns.Human brain mapping · 2021Article
- Prediction of baseline expressive and receptive language function in children with focal epilepsy using diffusion tractography-based deep learning network.Epilepsy & behavior : E&B · 2021Article
Corrections and comments
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Authors and funding
7 authors at 1 institution in 1 country.
Funding
Abstract
Prolonged seizures in children with focal epilepsy (FE) may impair language functions and often reoccur after surgical intervention. This study is aimed at developing a novel deep relational reasoning network to investigate whether conventional diffusion-weighted imaging connectome analysis can be improved when predicting expressive and receptive scores of preoperative language impairments and classifying postoperative seizure outcomes (seizure freedom or recurrence) in individual FE children. To deeply reason the dependencies of axonal connections that are sparsely distributed in the whole brain, this study proposes the "dilated CNN + RN", a dilated convolutional neural network (CNN) combined with a relation network (RN). The performance of the dilated CNN + RN was evaluated using whole brain connectome data from 51 FE children. It was found that when compared with other state-of-the-art algorithms, the dilated CNN + RN led to an average improvement of 90.2% and 97.3% in predicting expressive and receptive language scores, and 2.2% and 4% improvement in classifying seizure freedom and seizure recurrence, respectively. These improvements were independent of the prefixed connectome densities. Also, the dilated CNN + RN could provide an explainable artificial intelligence (AI) model by computing gradient-based regression/classification activation maps. This mapping analysis revealed left superior-medial frontal cortex, bilateral hippocampi, and cerebellum as crucial hubs, facilitating important connections that were most predictive of language function and seizure refractoriness after surgery.
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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.