AIMC Topic: Supranuclear Palsy, Progressive

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Machine Learning Models of Voxel-Level [F] Fluorodeoxyglucose Positron Emission Tomography Data Excel at Predicting Progressive Supranuclear Palsy Pathology.

Annals of neurology Aug 1, 2025
OBJECTIVE: To determine whether a machine learning model of voxel level [f]fluorodeoxyglucose positron emission tomography (PET) data could predict progressive supranuclear palsy (PSP) pathology, as well as outperform currently available biomarkers.
Aged, 80 and over Male Middle Aged Female Aged Positron-Emission Tomography Fluorodeoxyglucose F18 Supranuclear Palsy, Progressive Magnetic Resonance Imaging Radiopharmaceuticals Machine Learning Brain Humans
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Automated Imaging Differentiation for Parkinsonism.

JAMA neurology May 1, 2025
IMPORTANCE: Magnetic resonance imaging (MRI) paired with appropriate disease-specific machine learning holds promise for the clinical differentiation of Parkinson disease (PD), multiple system atrophy (MSA) parkinsonian variant, and progressive supra...
Prospective Studies Female Aged Humans Cohort Studies Support Vector Machine Magnetic Resonance Imaging Male Middle Aged Multiple System Atrophy Supranuclear Palsy, Progressive Parkinson Disease Parkinsonian Disorders Diagnosis, Differential Diffusion Magnetic Resonance Imaging
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Faster, More Practical, but Still Accurate: Deep Learning for Diagnosis of Progressive Supranuclear Palsy.

Radiology. Artificial intelligence May 1, 2024
Humans Deep Learning Supranuclear Palsy, Progressive
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Deep Learning-based Approach for Brainstem and Ventricular MR Planimetry: Application in Patients with Progressive Supranuclear Palsy.

Radiology. Artificial intelligence May 1, 2024
Purpose To develop a fast and fully automated deep learning (DL)-based method for the MRI planimetric segmentation and measurement of the brainstem and ventricular structures most affected in patients with progressive supranuclear palsy (PSP). Materi...
Supranuclear Palsy, Progressive Deep Learning Magnetic Resonance Imaging Cerebral Ventricles Brain Stem Image Interpretation, Computer-Assisted Male Middle Aged Reproducibility of Results Retrospective Studies Aged Female Humans
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Outgroup Machine Learning Approach Identifies Single Nucleotide Variants in Noncoding DNA Associated with Autism Spectrum Disorder.

Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing Jan 1, 2019
Autism spectrum disorder (ASD) is a heritable neurodevelopmental disorder affecting 1 in 59 children. While noncoding genetic variation has been shown to play a major role in many complex disorders, the contribution of these regions to ASD susceptibi...
Microsatellite Repeats Supranuclear Palsy, Progressive Genetic Association Studies Autism Spectrum Disorder Logistic Models Computational Biology Genetic Predisposition to Disease Whole Genome Sequencing Female CpG Islands MicroRNAs DNA Genetic Variation Polymorphism, Single Nucleotide RNA, Untranslated Machine Learning Humans Phenotype Male Cohort Studies Child Case-Control Studies Gene Regulatory Networks
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Differentiation of neurodegenerative parkinsonian syndromes by volumetric magnetic resonance imaging analysis and support vector machine classification.

Movement disorders : official journal of the Movement Disorder Society Oct 1, 2016
BACKGROUND: Clinical differentiation of parkinsonian syndromes is still challenging.
Parkinsonian Disorders Support Vector Machine Cerebellar Diseases Humans Supranuclear Palsy, Progressive Multiple System Atrophy Magnetic Resonance Imaging Brain
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