AIMC Topic: Parkinson Disease
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What the trained eye cannot see: Quantitative kinematics and machine learning detect movement deficits in early-stage Parkinson's disease from videos.
Parkinsonism & related disorders
Aug 14, 2024
BACKGROUND: Evaluation of disease severity in Parkinson's disease (PD) relies on motor symptoms quantification. However, during early-stage PD, these symptoms are subtle and difficult to quantify by experts, which might result in delayed diagnosis an...
Machine learning and wearable sensors for automated Parkinson's disease diagnosis aid: a systematic review.
Journal of neurology
Aug 14, 2024
BACKGROUND: The diagnosis of Parkinson's disease is currently based on clinical evaluation. Despite clinical hallmarks, unfortunately, the error rate is still significant. Low in-vivo diagnostic accuracy of clinical evaluation mainly relies on the la...
Wavelet-based selection-and-recalibration network for Parkinson's disease screening in OCT images.
Computer methods and programs in biomedicine
Aug 12, 2024
BACKGROUND AND OBJECTIVE: Parkinson's disease (PD) is one of the most prevalent neurodegenerative brain diseases worldwide. Therefore, accurate PD screening is crucial for early clinical intervention and treatment. Recent clinical research indicates ...
A Parkinson's Auxiliary Diagnosis Algorithm Based on a Hyperparameter Optimization Method of Deep Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 9, 2024
Parkinson's disease is a common mental disease in the world, especially in the middle-aged and elderly groups. Today, clinical diagnosis is the main diagnostic method of Parkinson's disease, but the diagnosis results are not ideal, especially in the ...
Deep Factor Learning for Accurate Brain Neuroimaging Data Analysis on Discrimination for Structural MRI and Functional MRI.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
Analysis of neuroimaging data (e.g., Magnetic Resonance Imaging, structural and functional MRI) plays an important role in monitoring brain dynamics and probing brain structures. Neuroimaging data are multi-featured and non-linear by nature, and it i...
Contrastive machine learning reveals Parkinson's disease specific features associated with disease severity and progression.
Communications biology
Aug 7, 2024
Parkinson's disease (PD) exhibits heterogeneity in terms of symptoms and prognosis, likely due to diverse neuroanatomical alterations. This study employs a contrastive deep learning approach to analyze Magnetic Resonance Imaging (MRI) data from 932 P...
SR-TWAS: leveraging multiple reference panels to improve transcriptome-wide association study power by ensemble machine learning.
Nature communications
Aug 5, 2024
Multiple reference panels of a given tissue or multiple tissues often exist, and multiple regression methods could be used for training gene expression imputation models for transcriptome-wide association studies (TWAS). To leverage expression imputa...
Simplification of Mobility Tests and Data Processing to Increase Applicability of Wearable Sensors as Diagnostic Tools for Parkinson's Disease.
Sensors (Basel, Switzerland)
Aug 1, 2024
Quantitative mobility analysis using wearable sensors, while promising as a diagnostic tool for Parkinson's disease (PD), is not commonly applied in clinical settings. Major obstacles include uncertainty regarding the best protocol for instrumented m...
Partial coherence enhances parallelized photonic computing.
Nature
Jul 31, 2024
Advancements in optical coherence control have unlocked many cutting-edge applications, including long-haul communication, light detection and ranging (LiDAR) and optical coherence tomography. Prevailing wisdom suggests that using more coherent light...
Attention-enhanced dilated convolution for Parkinson's disease detection using transcranial sonography.
Biomedical engineering online
Jul 31, 2024
BACKGROUND: Transcranial sonography (TCS) plays a crucial role in diagnosing Parkinson's disease. However, the intricate nature of TCS pathological features, the lack of consistent diagnostic criteria, and the dependence on physicians' expertise can ...
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