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6 papers · ranked by Valyu relevance

01
PPubMed5 Sep 2026
Deep learning-based multi-class misbehavior classification in fog-enabled vehicular ad hoc networks
Hadeer Kamal, Amira Y. Haikal, Mahmoud M. Saafan
Traffic collisions and congestion represent significant challenges within intelligent transportation systems (ITS). Consequently, a vehicular ad-hoc network (VANET) has been established. Numerous architectures have been incorporated into VANETs to manage the extensive data generated by vehicles. Collaboration with fog…
63relevance
02
BbioRxiv7 Sep 2026
BOTANIC-1: a series of long-context plant genomic foundation models in the agentic era
Amélie Barozet, Vincent Cabeli, Jean Ogier du Terrail, Alexey Rukhovich + 6 more
The development of climate-resilient crops would be greatly accelerated by models able to reason directly over plant genomic sequences and to pinpoint trait-associated regions or loci. Anticipating the impact of DNA base changes (variants) remains challenging, and understanding regulatory mechanisms is still an active…
60relevance
03
BbioRxiv11 Sep 2026
scOLAR: Ontology-Anchored Open-Set Annotation of Single-Cell RNA-seq Data
Yuqiao Liu, Siyu Yi, Hengchuang Yin, Wei Ju
Single-cell RNA sequencing profiles cellular heterogeneity at atlas scale, making automated annotation essential. However, target datasets often contain novel cell types missing from incomplete references. We present scOLAR, an ontology-guided open-set framework that learns prototypes over the Cell Ontology and uses…
60relevance
04
PPubMed7 Sep 2026
Interpretable deep neural network identifies robust biomarkers for diseases with mechanistic insights from omics data
Xiaoyue Hu, Yuhao Ma, Ruixing Ming, Heping Zhang + 1 more
Identifying essential biomarkers remains a core challenge in elucidating the pathogenic mechanisms and achieving precise diagnosis of complex diseases. Deep neural networks offer immense predictive power, yet their lack of interpretability severely limits downstream biological insight. Here, we introduce DeepVaris, an…
54relevance
05
PPubMed7 Sep 2026
Machine Learning for Autism Spectrum Disorder Prediction: A Review of Data Augmentation and Feature Selection Techniques
Sahar Alkhaibari, Feng Dong
Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by persistent difficulties in social communication, social interaction, and repetitive behaviors. Early and accurate diagnosis is essential but is often hindered by subjective clinical assessments, limited data availability, and…
51relevance
06
PPubMed6 Sep 2026
An Intraoperative EEG Biomarker for Postoperative Delirium Predicting Based on Interpretable Deep Learning Framework
Yinuo Zhang, Yan Zhu, Xinxin Zhang, Xinke Shen + 8 more
Postoperative delirium (POD) is a common complication in older surgical patients and substantially worsens clinical outcomes, yet existing intraoperative electroencephalography (EEG) monitoring tools lack spatial and temporal specificity, creating a need for interpretable biomarkers. We prospectively analyzed…
50relevance

Results for Multitask classification

Deep learning-based multi-class misbehavior classification in fog-enabled vehicular ad hoc networks

BOTANIC-1: a series of long-context plant genomic foundation models in the agentic era

scOLAR: Ontology-Anchored Open-Set Annotation of Single-Cell RNA-seq Data

Interpretable deep neural network identifies robust biomarkers for diseases with mechanistic insights from omics data

Machine Learning for Autism Spectrum Disorder Prediction: A Review of Data Augmentation and Feature Selection Techniques

An Intraoperative EEG Biomarker for Postoperative Delirium Predicting Based on Interpretable Deep Learning Framework

Deep learning-based multi-class misbehavior classification in fog-enabled vehicular ad hoc networks

BOTANIC-1: a series of long-context plant genomic foundation models in the agentic era

scOLAR: Ontology-Anchored Open-Set Annotation of Single-Cell RNA-seq Data

Interpretable deep neural network identifies robust biomarkers for diseases with mechanistic insights from omics data

Machine Learning for Autism Spectrum Disorder Prediction: A Review of Data Augmentation and Feature Selection Techniques

An Intraoperative EEG Biomarker for Postoperative Delirium Predicting Based on Interpretable Deep Learning Framework