ArticleFrontiers in neurology2020
Parkinson's Disease Diagnosis Using Neostriatum Radiomic Features Based on T2-Weighted Magnetic Resonance Imaging.
Article in Frontiers in neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
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The trial behind it
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Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Detection of parkinson's disease with neuroimaging modalities using machine learning and artificial intelligence: a systematic review.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Pooled it
- The differential diagnosis value of radiomics-based machine learning in Parkinson's disease: a systematic review and meta-analysis.Frontiers in aging neuroscience · 2023Pooled it
- A Brainstem Radiomics Framework to Distinguish Progressive Supranuclear Palsy from Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2026Article
- Predicting motor function improvement following deep brain stimulation of the subthalamic nucleus for Parkinson's disease based on STN-T2MRI radiomics.Journal of Parkinson's disease · 2025Article
- Harnessing routine MRI for the early screening of Parkinson's disease: a multicenter machine learning study using T2-weighted FLAIR imaging.Insights into imaging · 2025Article
- Evaluation of neostriatum changes in Crohn's disease: a multimodal brain magnetic resonance imaging study.Quantitative imaging in medicine and surgery · 2024Article
- Radiomics score derived from T1-w/T2-w ratio image can predict motor symptom progression in Parkinson's disease.European radiology · 2024Article
- Multi-modality radiomics of conventional T1 weighted and diffusion tensor imaging for differentiating Parkinson's disease motor subtypes in early-stages.Scientific reports · 2024Article
- Automatic substantia nigra segmentation with Swin-Unet in susceptibility- and T2-weighted imaging: application to Parkinson disease diagnosis.Quantitative imaging in medicine and surgery · 2024Article
- A rapid multi-parametric quantitative MR imaging method to assess Parkinson's disease: a feasibility study.BMC medical imaging · 2024Article
- An interpretable multiparametric radiomics model of basal ganglia to predict dementia conversion in Parkinson's disease.NPJ Parkinson's disease · 2023Article
- Ferroptosis: a new regulatory mechanism in neuropathic pain.Frontiers in aging neuroscience · 2023Review
- Asymmetry of radiomics features in the white matter of patients with primary progressive aphasia.Frontiers in aging neuroscience · 2023Article
- Automatic diagnosis of Parkinson's disease using artificial intelligence base on routine T1-weighted MRI.Frontiers in medicine · 2023Article
- Diffusion Tensor Imaging Radiomics for Diagnosis of Parkinson's Disease.Brain sciences · 2022Article
- The impact of harmonization on radiomic features in Parkinson's disease and healthy controls: A multicenter study.Frontiers in neuroscience · 2022Article
- Detection of Microstructural Medial Prefrontal Cortex Changes Using Magnetic Resonance Imaging Texture Analysis in a Post-Traumatic Stress Disorder Rat Model.Frontiers in psychiatry · 2022Article
- Radiomics on routine T1-weighted MRI can delineate Parkinson's disease from multiple system atrophy and progressive supranuclear palsy.European radiology · 2021Article
- Aberrant functional connectivity and activity in Parkinson's disease and comorbidity with depression based on radiomic analysis.Brain and behavior · 2021Article
- CT Angiography-Based Radiomics for Classification of Intracranial Aneurysm Rupture.Frontiers in neurology · 2021Article
Corrections and comments
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Authors and funding
5 authors.
Funding
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Abstract
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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.