ReviewBrain sciences2024
Artificial Intelligence-Based Methodologies for Early Diagnostic Precision and Personalized Therapeutic Strategies in Neuro-Ophthalmic and Neurodegenerative Pathologies.
Review in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 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
18 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- The role of AI-assisted drug repurposing in neurological disorders: a systematic review of validation strategies, challenges and opportunities.Journal of nanobiotechnology · 2026Pooled it
- Diagnostic performance of neuroimaging modalities for epileptogenic focus localization: A systematic review.Epilepsia open · 2026Pooled it
- Toward Long-Term Visual Field Appearance Forecasting Using Artificial Intelligence for Ophthalmic Education and Diagnosis.Ophthalmology science · 2026Article
- Review
- A deep-SVM hybrid framework with enhanced EEG feature engineering and SHAP-based explainability for Alzheimer's classification.Scientific reports · 2026Article
- Revolutionizing Neurodegenerative Disease Management: The Synergy of AI and Pharmacy.Current aging science · 2026Review
- Brain Tumors, AI and Psychiatry: Predicting Tumor-Associated Psychiatric Syndromes with Machine Learning and Biomarkers.International journal of molecular sciences · 2025Review
- Precision Recovery After Spinal Cord Injury: Integrating CRISPR Technologies, AI-Driven Therapeutics, Single-Cell Omics, and System Neuroregeneration.International journal of molecular sciences · 2025Review
- Doxycycline: An essential tool for Alzheimer's disease.Biomedicine & pharmacotherapy = Biomedecine & pharmacotherapie · 2025Review
- Tear Film and Keratitis in Space: Fluid Dynamics and Nanomedicine Strategies for Ocular Protection in Microgravity.Pharmaceutics · 2025Review
- Next-Generation Biomaterials for Load-Bearing Tissue Interfaces: Sensor-Integrated Scaffolds and Mechanoadaptive Constructs for Skeletal Regeneration.Journal of functional biomaterials · 2025Review
- Perspectives in Amyotrophic Lateral Sclerosis: Biomarkers, Omics, and Gene Therapy Informing Disease and Treatment.International journal of molecular sciences · 2025Review
- Review
- Imaging biomarkers in optic neuritis: current tools and future directions.Frontiers in neurology · 2025Review
- Advancements in deep learning for early diagnosis of Alzheimer's disease using multimodal neuroimaging: challenges and future directions.Frontiers in neuroinformatics · 2025Review
- Development of Brain Permeable Drugs and Novel Strategies to Overcome the Brain Barriers for Treatment Purposes.Current pharmaceutical design · 2025Review
- Deep Learning and The Retina: A New Frontier in Multiple Sclerosis Diagnosis.Current health sciences journalReview
- Neuroimmunological overlap syndromes in optic neuritis, myelitis, and connective tissue diseases.Frontiers in neurologyReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advancements in neuroimaging, particularly diffusion magnetic resonance imaging (MRI) techniques and molecular imaging with positron emission tomography (PET), have significantly enhanced the early detection of biomarkers in neurodegenerative and neuro-ophthalmic disorders. These include Alzheimer's disease, Parkinson's disease, multiple sclerosis, neuromyelitis optica, and myelin oligodendrocyte glycoprotein antibody disease. This review highlights the transformative role of advanced diffusion MRI techniques-Neurite Orientation Dispersion and Density Imaging and Diffusion Kurtosis Imaging-in identifying subtle microstructural changes in the brain and visual pathways that precede clinical symptoms. When integrated with artificial intelligence (AI) algorithms, these techniques achieve unprecedented diagnostic precision, facilitating early detection of neurodegeneration and inflammation. Additionally, next-generation PET tracers targeting misfolded proteins, such as tau and alpha-synuclein, along with inflammatory markers, enhance the visualization and quantification of pathological processes in vivo. Deep learning models, including convolutional neural networks and multimodal transformers, further improve diagnostic accuracy by integrating multimodal imaging data and predicting disease progression. Despite challenges such as technical variability, data privacy concerns, and regulatory barriers, the potential of AI-enhanced neuroimaging to revolutionize early diagnosis and personalized treatment in neurodegenerative and neuro-ophthalmic disorders is immense. This review underscores the importance of ongoing efforts to validate, standardize, and implement these technologies to maximize their clinical impact.
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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.