SynthesisFrontiers in neuroscience2024
The identification of cognitive impairment in Parkinson's disease using biofluids, neuroimaging, and artificial intelligence.
Synthesis in Frontiers in neuroscience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
9 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Best practice guidelines for the diagnosis, evaluation, and management of cognitive disorders in Parkinson's disease.Age and ageing · 2026Guideline
- Potential protein blood-based biomarkers for cognitive dysfunction in Parkinson's disease: a systematic review and network meta-analysis.Frontiers in aging neuroscience · 2026Pooled it
- Quantitative susceptibility mapping and MRS-based multimodal machine learning for early Parkinson's disease classification.NPJ Parkinson's disease · 2026Article
- Interpreting the risk of postoperative post-neuraxial puncture-site pain after cesarean section: a machine learning approach evaluating nalbuphine infiltration along the epidural puncture tract in a prospective observational cohort.Frontiers in medicine · 2026Article
- Predicting Cognitive Decline in Parkinson's Disease Using Artificial Neural Networks: An Explainable AI Approach.Brain sciences · 2025Article
- Using machine learning for detection of Parkinson's disease and mild cognitive impairment.PloS one · 2025Article
- Construction of a prediction and visualization system for cognitive impairment in elderly COPD patients based on self-assigning feature weights and residual evolution model.Frontiers in artificial intelligence · 2025Article
- What can we do to enhance cognitive care in Parkinson's disease?Alzheimer's & dementia (Amsterdam, Netherlands)Article
- Diagnosis, evaluation, and management of cognitive disorders in Parkinson's disease: Consensus recommendations from a modified Delphi process.Alzheimer's & dementia (Amsterdam, Netherlands)Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: Parkinson's disease (PD) is a neurodegenerative movement disorder causing severe disability and cognitive impairment as the disease progresses. It is necessary to develop biomarkers for cognitive decline in PD for earlier detection and prediction of disease progression. Methods: We reviewed literature which used artificial intelligence-based techniques, which can be more sensitive than other analyses, to determine potential biomarkers for cognitive impairment in PD. Results: We found that combining biomarker types, including those from neuroimaging and biofluids, resulted in higher accuracy. Focused analysis on each biomarker type revealed that using structural and functional magnetic resonance imaging (MRI) resulted in accuracy and area under the curve (AUC) values above 80%/0.80, and that beta-amyloid-42 and tau were able to classify PD subjects by cognitive function with accuracy and AUC values above 90%/0.90. Discussion: We can conclude that applying both blood-based and imaging-based biomarkers may improve diagnostic accuracy and prediction of cognitive impairment in PD.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.