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Journal of molecular neuroscience : MN

Showing 1 to 10 of 10 articles

Discovering Novel Biomarkers and Potential Therapeutic Targets of Amyotrophic Lateral Sclerosis Through Integrated Machine Learning and Gene Expression Profiling.

Journal of molecular neuroscience : MN Apr 30, 2025
Amyotrophic lateral sclerosis (ALS) is a progressive neurodegenerative disorder that has multiple factors that make its molecular pathogenesis difficult to understand and its diagnosis and treatment during the early stages difficult to determine. Dis...
Amyotrophic Lateral Sclerosis Tumor Suppressor Proteins Receptors, Nicotinic Humans Machine Learning Biomarkers Gene Expression Profiling Transcriptome Membrane Proteins
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Identification and Validation of Glycosylation‑Related Genes in Ischemic Stroke Based on Bioinformatics and Machine Learning.

Journal of molecular neuroscience : MN Apr 29, 2025
Ischemic stroke (IS) constitutes a severe neurological disorder with restricted treatment alternatives. Recent investigations have disclosed that glycosylation is closely associated with the occurrence and outcome of IS. Nevertheless, data on the tra...
Ubiquitin-Conjugating Enzymes Computational Biology Glycosylation Ischemic Stroke Transcriptome Gene Regulatory Networks Humans Machine Learning
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Identification of Recurrence-associated Gene Signatures and Machine Learning-based Prediction in IDH-Wildtype Histological Glioblastoma.

Journal of molecular neuroscience : MN Apr 14, 2025
Glioblastoma (GBM) is a highly aggressive brain tumor with frequent recurrence, yet the molecular mechanisms driving recurrence remain poorly understood. Identifying recurrence-associated genes may improve prognosis and treatment strategies. We appli...
Humans Machine Learning Female Transcriptome Glioblastoma Neoplasm Recurrence, Local Isocitrate Dehydrogenase Biomarkers, Tumor Brain Neoplasms Male
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A Novel Fusion Framework Combining Graph Embedding Class-Based Convolutional Recurrent Attention Network with Brown Bear Optimization Algorithm for EEG-Based Parkinson's Disease Recognition.

Journal of molecular neuroscience : MN Mar 15, 2025
Parkinson's disease recognition (PDR) involves identifying Parkinson's disease using clinical evaluations, imaging studies, and biomarkers, focusing on early symptoms like tremors, rigidity, and bradykinesia to facilitate timely treatment. However, d...
Parkinson Disease Electroencephalography Datasets as Topic Machine Learning Algorithms Humans Convolutional Neural Networks
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Identification of Novel Biomarkers for Ischemic Stroke Through Integrated Bioinformatics Analysis and Machine Learning.

Journal of molecular neuroscience : MN Jan 25, 2025
Ischemic stroke leads to permanent damage to the affected brain tissue, with strict time constraints for effective treatment. Predictive biomarkers demonstrate great potential in the clinical diagnosis of ischemic stroke, significantly enhancing the ...
Humans Machine Learning Biomarkers Ischemic Stroke Gene Regulatory Networks Computational Biology
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Deciphering Necroptosis-Associated Molecular Subtypes in Acute Ischemic Stroke Through Bioinformatics and Machine Learning Analysis.

Journal of molecular neuroscience : MN Jan 2, 2025
Acute ischemic stroke (AIS) is a severe disorder characterized by complex pathophysiological processes, which can lead to disability and death. This study aimed to determine necroptosis-associated genes in acute ischemic stroke (AIS) and to investiga...
Humans Ischemic Stroke Machine Learning Transcriptome Protein Interaction Maps Gene Regulatory Networks Computational Biology Necroptosis
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Predictive Model to Identify the Long Time Survivor in Patients with Glioblastoma: A Cohort Study Integrating Machine Learning Algorithms.

Journal of molecular neuroscience : MN Apr 25, 2024
We aimed to develop and validate a predictive model for identifying long-term survivors (LTS) among glioblastoma (GB) patients, defined as those with an overall survival (OS) of more than 3 years. A total of 293 GB patients from CGGA and 169 from TCG...
Humans Machine Learning Brain Neoplasms Male Algorithms Female Glioblastoma Tissue Inhibitor of Metalloproteinase-1 Cancer Survivors Middle Aged Transcriptome Nomograms
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Application of Artificial Neural Network for Prediction of Risk of Multiple Sclerosis Based on Single Nucleotide Polymorphism Genotypes.

Journal of molecular neuroscience : MN Mar 9, 2020
The artificial neural network (ANN) is a sort of machine learning method which has been used in determination of risk of human disorders. In the current investigation, we have created an ANN and trained it based on the genetic data of 401 multiple sc...
Adult Male Genome-Wide Association Study Neural Networks, Computer Software Female Polymorphism, Single Nucleotide Genotype Multiple Sclerosis Humans
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Application of Single-Nucleotide Polymorphisms in the Diagnosis of Autism Spectrum Disorders: A Preliminary Study with Artificial Neural Networks.

Journal of molecular neuroscience : MN Apr 1, 2019
Autism spectrum disorder (ASD) includes different neurodevelopmental disorders characterized by deficits in social communication, and restricted, repetitive patterns of behavior, interests or activities. Based on the importance of early diagnosis for...
Child Polymorphism, Single Nucleotide Genetic Testing Synaptosomal-Associated Protein 25 Receptors, GABA-A Sensitivity and Specificity Receptors, Metabotropic Glutamate Male Humans Deep Learning Autism Spectrum Disorder Female
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Editorial: Designing a Protocol Adopting an Artificial Intelligence (AI)-Driven Approach for Early Diagnosis of Late-Onset Alzheimer's Disease.

Journal of molecular neuroscience : MN Jul 1, 2021
Mutation Models, Biological Patient Selection Ethnicity Early Diagnosis Asian People Alzheimer Disease Mobile Applications Cognition Observational Studies as Topic Language Case-Control Studies Wearable Electronic Devices Clinical Trial Protocols as Topic Humans Behavior Artificial Intelligence Mental Status and Dementia Tests Prospective Studies Late Onset Disorders Biomarkers Hong Kong Medical History Taking Memory
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