Mammalian genome : official journal of the International Mammalian Genome Society
Jan 16, 2026
Neurodegenerative diseases (NDDs), including Alzheimer's disease (AD) and Parkinson's disease (PD), are major public health challenges lacking effective therapies. To identify potential drug targets, we integrated large-scale genome-wide association ...
BACKGROUND: Parkinson disease (PD) presents diagnostic challenges due to its heterogeneous motor and nonmotor manifestations. Traditional machine learning (ML) approaches have been evaluated on structured clinical variables. However, the diagnostic u...
Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology
Jan 14, 2026
The application of machine learning (ML) and artificial intelligence (AI) algorithms in medical imaging is an emerging area of interest, particularly in the context of clinical decision-making. Here, we report on the overall performance (i.e., sensit...
BACKGROUND: Accurate diagnosis of Parkinson's Disease (PD) remains challenging due to its biological complexity. Integrating machine learning with multi-omics and network topological analyses may enhance diagnostic precision.
Progress in neuro-psychopharmacology & biological psychiatry
Dec 4, 2025
PURPOSE: Metabolic disturbances are hallmark pathological features of Parkinson's disease (PD) and can be noninvasively captured by arterial spin labeling (ASL). However, the metabolic pattern of disconnections beyond regional alterations remains sca...
Parkinson's disease (PD) is a neurodegenerative disorder characterized by dopaminergic neuron loss and neuroinflammation, with emerging roles of peripheral immune dysregulation in disease progression. This study aimed to investigate the regulatory ne...
Parkinson's disease is one of the most common and complex neurodegenerative diseases, characterized by remarkable motor and cognitive decline. As it is a highly heterogeneous disorder, i.e., the specific symptoms, their severity, and their progressio...
PURPOSE: This study aims to evaluate the diagnostic performance of PET-based artificial intelligence (AI) for differentiating Parkinson's disease (PD) from normal controls (NC) or atypical parkinsonism (AP).
Parkinson's disease (PD) is a brain disorder, that affects a person's body movement causing stiffness, shaking and imbalance. Earlier detection of PD is a challenging task for researchers. In this paper, earlier detection of PD is performed using the...
BACKGROUND: Machine learning shows great potential in science but struggles with complex, high-dimensional multi-omics data. PD progression is long, diagnosed mainly by clinical signs. This paper proposes a novel decision fusion method to improve the...
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