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New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson's disease
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 …
synaptic dysfunction and cognitive defects. Despite the advancements in treatment …
Machine learning models for diagnosis and prognosis of Parkinson's disease using brain imaging: general overview, main challenges, and future directions
Parkinson's disease (PD) is a progressive and complex neurodegenerative disorder
associated with age that affects motor and cognitive functions. As there is currently no cure …
associated with age that affects motor and cognitive functions. As there is currently no cure …
Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis
The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting
counseling and inflating the number of patients needed to test potential neuroprotective …
counseling and inflating the number of patients needed to test potential neuroprotective …
[HTML][HTML] An artificial intelligence-based decision support system for early and accurate diagnosis of Parkinson's Disease
Abstract People with Parkinson's Disease (PD) might struggle with sadness, restlessness, or
difficulty speaking, chewing, or swallowing. A diagnosis can be challenging because there is …
difficulty speaking, chewing, or swallowing. A diagnosis can be challenging because there is …
Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker
Short-term mortality risk, which is indicative of individual frailty, serves as a marker for aging.
Previous age clocks focused on predicting either chronological age or longer-term mortality …
Previous age clocks focused on predicting either chronological age or longer-term mortality …
Identification of Parkinson's disease subtypes from resting‐state electroencephalography
Background Parkinson's disease (PD) patients present with a heterogeneous clinical
phenotype, including motor, cognitive, sleep, and affective disruptions. However, this …
phenotype, including motor, cognitive, sleep, and affective disruptions. However, this …
Federated Learning for multi-omics: a performance evaluation in Parkinson's disease
While machine learning (ML) research has recently grown more in popularity, its application
in the omics domain is constrained by access to sufficiently large, high-quality datasets …
in the omics domain is constrained by access to sufficiently large, high-quality datasets …
Application of Aligned-UMAP to longitudinal biomedical studies
High-dimensional data analysis starts with projecting the data to low dimensions to visualize
and understand the underlying data structure. Several methods have been developed for …
and understand the underlying data structure. Several methods have been developed for …
Genetics in Parkinson's disease, state-of-the-art and future perspectives
L Trevisan, A Gaudio, E Monfrini… - British Medical …, 2024 - academic.oup.com
Background Parkinson's disease (PD) is the second most common neurodegenerative
disorder and is clinically characterized by the presence of motor (bradykinesia, rigidity, rest …
disorder and is clinically characterized by the presence of motor (bradykinesia, rigidity, rest …
Refining the clinical diagnosis of Parkinson's disease
Our ability to define, understand, and classify Parkinson's disease (PD) has undergone
significant changes since the disorder was first described in 1817. Clinical features and …
significant changes since the disorder was first described in 1817. Clinical features and …