AIMC Topic: Parkinson Disease
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Accurate measurement of magnetic resonance parkinsonism index by a fully automatic and deep learning quantification pipeline.
European radiology
Jul 22, 2023
OBJECTIVES: This study aims at a fully automatic pipeline for measuring the magnetic resonance parkinsonism index (MRPI) using deep learning methods.
Probing the molecular mechanisms of α-synuclein inhibitors unveils promising natural candidates through machine-learning QSAR, pharmacophore modeling, and molecular dynamics simulations.
Molecular diversity
Jul 18, 2023
Parkinson's disease is characterized by a multifactorial nature that is linked to different pathways. Among them, the abnormal deposition and accumulation of α-synuclein fibrils is considered a neuropathological hallmark of Parkinson's disease. Sever...
New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson's disease.
Ageing research reviews
Jul 8, 2023
Parkinson's disease (PD) is characterized by the loss of neuronal cells, which leads to synaptic dysfunction and cognitive defects. Despite the advancements in treatment strategies, the management of PD is still a challenging event. Early prediction ...
An automatic interpretable deep learning pipeline for accurate Parkinson's disease diagnosis using quantitative susceptibility mapping and T1-weighted images.
Human brain mapping
Jun 19, 2023
Parkinson's disease (PD) diagnosis based on magnetic resonance imaging (MRI) is still challenging clinically. Quantitative susceptibility maps (QSM) can potentially provide underlying pathophysiological information by detecting the iron distribution ...
Denoising approach with deep learning-based reconstruction for neuromelanin-sensitive MRI: image quality and diagnostic performance.
Japanese journal of radiology
May 31, 2023
PURPOSE: Neuromelanin-sensitive MRI (NM-MRI) has proven useful for diagnosing Parkinson's disease (PD) by showing reduced signals in the substantia nigra (SN) and locus coeruleus (LC), but requires a long scan time. The aim of this study was to asses...
Automatic detection of Parkinson's disease from power spectral density of electroencephalography (EEG) signals using deep learning model.
Physical and engineering sciences in medicine
May 28, 2023
Parkinson's disease (PD) is characterized by slowed movements, speech disorders, an inability to control muscle movements, and tremors in the hands and feet. In the early stages of PD, the changes in these motor signs are very vague, so an objective ...
Diagnosis of Parkinson's Disease via the Metabolic Fingerprint in Saliva by Deep Learning.
Small methods
May 26, 2023
Parkinson's disease (PD) is the second cause of the neurodegenerative disorder, affecting over 6 million people worldwide. The World Health Organization estimated that population aging will cause global PD prevalence to double in the coming 30 years....
Multi-Modal Deep Learning Diagnosis of Parkinson's Disease-A Systematic Review.
IEEE transactions on neural systems and rehabilitation engineering : a publication of the IEEE Engineering in Medicine and Biology Society
May 25, 2023
Parkinson's Disease (PD) is among the most frequent neurological disorders. Approaches that employ artificial intelligence and notably deep learning, have been extensively embraced with promising outcomes. This study dispenses an exhaustive review be...
msQSM: Morphology-based self-supervised deep learning for quantitative susceptibility mapping.
NeuroImage
May 21, 2023
Quantitative susceptibility mapping (QSM) has been applied to the measurement of iron deposition and the auxiliary diagnosis of neurodegenerative disease. There still exists a dipole inversion problem in QSM reconstruction. Recently, deep learning ap...
Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.
Neuroradiology
May 20, 2023
PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (I-FP-CIT) single-photon emission computerized tomography (SPECT) can eval...
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