New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson's disease

R Gupta, S Kumari, A Senapati, RK Ambasta… - Ageing research …, 2023 - Elsevier
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 …

Machine learning models for diagnosis and prognosis of Parkinson's disease using brain imaging: general overview, main challenges, and future directions

B Garcia Santa Cruz, A Husch, F Hertel - Frontiers in Aging …, 2023 - frontiersin.org
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 …

Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis

T Hähnel, T Raschka, S Sapienza, J Klucken… - npj Parkinson's …, 2024 - nature.com
The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting
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

TR Mahesh, R Bhardwaj, SB Khan, NA Alkhaldi… - Decision Analytics …, 2024 - Elsevier
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 …

Deep learning-based prediction of one-year mortality in Finland is an accurate but unfair aging marker

A Vabalas, T Hartonen, P Vartiainen, S Jukarainen… - Nature Aging, 2024 - nature.com
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 …

Identification of Parkinson's disease subtypes from resting‐state electroencephalography

S Yassine, U Gschwandtner, M Auffret… - Movement …, 2023 - Wiley Online Library
Background Parkinson's disease (PD) patients present with a heterogeneous clinical
phenotype, including motor, cognitive, sleep, and affective disruptions. However, this …

Federated Learning for multi-omics: a performance evaluation in Parkinson's disease

BP Danek, MB Makarious, A Dadu, D Vitale, PS Lee… - Patterns, 2024 - cell.com
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 …

Application of Aligned-UMAP to longitudinal biomedical studies

A Dadu, VK Satone, R Kaur, MJ Koretsky, H Iwaki… - Patterns, 2023 - cell.com
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 …

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 …

Refining the clinical diagnosis of Parkinson's disease

E Mulroy, R Erro, KP Bhatia, M Hallett - Parkinsonism & Related Disorders, 2024 - Elsevier
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 …