ReviewNature reviews. Neurology2020
Applications of machine learning to diagnosis and treatment of neurodegenerative diseases.
Review in Nature reviews. Neurology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 207 papers, 4 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
207 citing papers in PubMed, 4 syntheses or guidelines pooled it, 572 citations in OpenAlex.
- Performance of Machine Learning in Diagnosing KRAS (Kirsten Rat Sarcoma) Mutations in Colorectal Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- The Impact and Role of Artificial Intelligence (AI) in Healthcare: Systematic Review.Current topics in medicinal chemistry · 2025Pooled it
- Critical Analysis of the Current Medical Image-Based Processing Techniques for Automatic Disease Evaluation: Systematic Literature Review.Sensors (Basel, Switzerland) · 2022Pooled it
- Diagnostic accuracy of keystroke dynamics as digital biomarkers for fine motor decline in neuropsychiatric disorders: a systematic review and meta-analysis.Scientific reports · 2022Pooled it
- Predictors of rituximab efficacy in systemic sclerosis-associated interstitial lung disease: machine-learning analysis of the DESIRES trial.Rheumatology (Oxford, England) · 2025Trial
- Digital twin for neurological conditions: a systematic scoping review.Biomedical engineering letters · 2026Review
- Towards neuromorphic neurotechnologies: integrating brain-inspired computing with brain-computer interfaces.npj biomedical innovations · 2026Review
- The role of "red flags" in the diagnostic work-up of hereditary transthyretin amyloidosis: a study using a machine-learning approach.Neurological sciences : official journal of the Italian Neurological Society and of the Italian Society of Clinical Neurophysiology · 2026Article
- Quantifying generalization error in machine learning prediction of cognitive decline.The journal of prevention of Alzheimer's disease · 2026Article
- Hierarchical sparse spatiotemporal graph neural network for brain graph classification.iScience · 2026Article
- Explainable machine learning identifies candidate shared neuroanatomical features in Alzheimer's and Parkinson's via importance inversion transfer.bioRxiv : the preprint server for biology · 2026Article
- Machine-Learning-Based Targeted Plasma Proteomic Analysis for Predicting Motor Progression in Parkinson's Disease: An Interpretable Approach to Personalized Disease Management.Bioengineering (Basel, Switzerland) · 2026Article
- A parsimonious six-predictor model for memory decline: cross-population validation in Chinese and Japanese aging cohorts.GeroScience · 2026Article
- Development and internal validation of a machine learning-based model for predicting 2-year mortality in interstitial lung disease.Respiratory research · 2026Article
- A machine learning model based on routine blood-derived indices for early arterial stiffness prediction in the community.Lipids in health and disease · 2026Article
- Deep learning approaches to map individual differences in macroscopic neural structure with variations in spatial navigation behavior.Neuropsychologia · 2026Article
- Structural Alterations and Cognitive Impairment in Late-Onset Depression: A Reverse Correlation Analysis.Alpha psychiatry · 2026Article
- Early screening of mild cognitive impairment based on eye-tracking technology: a cross-sectional study.Aging clinical and experimental research · 2026Article
- Predicting Continuous Cognitive Decline: The Generalizability of a Multimodal Machine Learning Approach Including Structural MRI and Non-Brain Data.medRxiv : the preprint server for health sciences · 2026Article
- Building the next frontier: Artificial intelligence in 3D-printed medicines.Biomaterials translational · 2026Review
147 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 2 institutions in 1 country.
Funding
Abstract
Globally, there is a huge unmet need for effective treatments for neurodegenerative diseases. The complexity of the molecular mechanisms underlying neuronal degeneration and the heterogeneity of the patient population present massive challenges to the development of early diagnostic tools and effective treatments for these diseases. Machine learning, a subfield of artificial intelligence, is enabling scientists, clinicians and patients to address some of these challenges. In this Review, we discuss how machine learning can aid early diagnosis and interpretation of medical images as well as the discovery and development of new therapies. A unifying theme of the different applications of machine learning is the integration of multiple high-dimensional sources of data, which all provide a different view on disease, and the automated derivation of actionable insights.
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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.