ArticleFrontiers in aging neuroscience2018
Radiomic Features of Hippocampal Subregions in Alzheimer's Disease and Amnestic Mild Cognitive Impairment.
Article in Frontiers in aging neuroscience, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 51 papers, 1 of them a synthesis that pooled it.
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Who cites it
51 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Diagnostic performance of MRI radiomics for classification of Alzheimer's disease, mild cognitive impairment, and normal subjects: a systematic review and meta-analysis.Aging clinical and experimental research · 2023Pooled it
- Textural features of the frontal white matter could be used to discriminate amnestic mild cognitive impairment patients from the normal population.Brain and behavior · 2023Trial
- Article
- Progressive modeling of multiscale hippocampal subfield structural representation improves the prediction performance of mild cognitive impairment in type 2 diabetes.European archives of psychiatry and clinical neuroscience · 2026Article
- Integration of glymphatic system function and hippocampal radiomics for diagnosis and conversion prediction of Alzheimer's disease.BMC medical imaging · 2026Article
- Reducing Educational Bias in Cognitive Assessment via Dynamic Support Vector Machine Weighting: Validation Study on an Education-Stratified Dataset.JMIR rehabilitation and assistive technologies · 2026Article
- Hippocampal texture asymmetry features onFrontiers in immunology · 2026Article
- Ultrasound-based radiomics and machine learning for enhanced diagnosis of knee osteoarthritis: Evaluation of diagnostic accuracy, sensitivity, specificity, and predictive value.European journal of radiology open · 2025Article
- Deep learning-based CAD system for Alzheimer's diagnosis using deep downsized KPLS.Scientific reports · 2025Article
- Microstructural grey matter alterations in patients with behavioural variant frontotemporal dementia.Brain communications · 2025Article
- Leveraging hand-crafted radiomics on multicenter FLAIR MRI for predicting disability worsening in people with multiple sclerosis.Frontiers in neuroscience · 2025Article
- Early prediction of Alzheimer's disease using artificial intelligence and cortical features on T1WI sequences.Frontiers in neurology · 2025Article
- Prediction models for cognitive impairment in middle-aged patients with cerebral small vessel disease.Frontiers in neurology · 2025Article
- Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study.Journal of pain research · 2025Article
- Morphological similarity and white matter structural mapping of new daily persistent headache: a structural connectivity and tract-specific study.The journal of headache and pain · 2024Article
- Disparities in the diagnostic efficacy of radiomics models in predicting various degrees of cognitive impairment in patients with cerebral small vessel disease.BMC medical imaging · 2024Article
- Beyond Macrostructure: Is There a Role for Radiomics Analysis in Neuroimaging ?Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine · 2024Review
- Multiparametric hippocampal signatures for early diagnosis of Alzheimer's disease usingCNS neuroscience & therapeutics · 2024Article
- Comparison of approaches to control for intracranial volume in research on the association of brain volumes with cognitive outcomes.Human brain mapping · 2024Article
- Morphological connectivity differences in Alzheimer's disease correlate with gene transcription and cell-type.Human brain mapping · 2023Article
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13 authors.
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Abstract
Alzheimer's disease (AD) is characterized by progressive dementia, especially in episodic memory, and amnestic mild cognitive impairment (aMCI) is associated with a high risk of developing AD. Hippocampal atrophy/shape changes are believed to be the most robust magnetic resonance imaging (MRI) markers for AD and aMCI. Radiomics, a method of texture analysis, can quantitatively examine a large set of features and has previously been successfully applied to evaluate imaging biomarkers for AD. To test whether radiomic features in the hippocampus can be employed for early classification of AD and aMCI, 1692 features from the caudal and head parts of the bilateral hippocampus were extracted from 38 AD patients, 33 aMCI patients and 45 normal controls (NCs). One way analysis of variance (ANOVA) showed that 111 features exhibited statistically significant group differences (
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