Neurodiagnoses AI is an open-source, AI-driven framework designed to enhance the diagnosis and prognosis of central nervous system (CNS) disorders. Building upon the Florey Dementia Index (FDI) methodology, it now encompasses a broader spectrum of neurological conditions. The system integrates multimodal data sources—including EEG, neuroimaging, biomarkers, and genetics—and employs machine learning models to deliver explainable, real-time diagnostic insights. A key feature of this framework is the incorporation of the Generalized Neuro Biomarker Ontology Categorization (Neuromarker), which standardizes biomarker classification across all neurodegenerative diseases, facilitating cross-disease AI training.

Neuromarker: Generalized Biomarker Ontology

Neuromarker extends the Common Alzheimer’s Disease Research Ontology (CADRO) into a comprehensive biomarker categorization framework applicable to all neurodegenerative diseases (NDDs). This ontology enables standardized classification, AI-based feature extraction, and seamless multimodal data integration.

Core Biomarker Categories

Within the Neurodiagnoses AI framework, biomarkers are categorized as follows:

Integrating External Databases into Neurodiagnoses

To enhance diagnostic precision, Neurodiagnoses AI incorporates data from multiple biomedical and neurological research databases. Researchers can integrate external datasets by following these steps:

1. Register for Access

   • Each external database requires individual registration and access approval.
   • Ensure compliance with ethical approvals and data usage agreements before integrating datasets into Neurodiagnoses.
   • Some repositories may require a Data Usage Agreement (DUA) for sensitive medical data.

2. Download & Prepare Data

   • Download datasets while adhering to database usage policies.

   • Ensure files meet Neurodiagnoses format requirements:

     Data Type	Accepted Formats
     Tabular Data	.csv, .tsv
     Neuroimaging	.nii, .dcm
     Genomic Data	.fasta, .vcf
     Clinical Metadata	.json, .xml

   • Mandatory Fields for Integration:

     • Subject ID: Unique patient identifier
     • Diagnosis: Standardized disease classification
     • Biomarkers: CSF, plasma, or imaging biomarkers
     • Genetic Data: Whole-genome or exome sequencing
     • Neuroimaging Metadata: MRI/PET acquisition parameters

3. Upload Data to Neurodiagnoses

   • Option 1: Upload to EBRAINS Bucket

     • Location: EBRAINS Neurodiagnoses Bucket
     • Ensure correct metadata tagging before submission.

   • Option 2: Contribute via GitHub Repository

     • Location: GitHub Data Repository
     • Create a new folder under /data/ and include a dataset description.
     • For large datasets, contact project administrators before uploading.

4. Integrate Data into AI Models

   • Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
   • Standardize neuroimaging and biomarker formats using harmonization tools.
   • Utilize machine learning models to handle missing data and feature extraction.
   • Train AI models with newly integrated patient cohorts.

   Reference: See docs/data_processing.md for detailed instructions.

AI-Driven Biomarker Categorization

Neurodiagnoses employs advanced AI models for biomarker classification:

Collaboration & Partnerships

Neurodiagnoses actively seeks partnerships with data providers to:

• Enable API-based data integration for real-time processing.
• Co-develop harmonized AI-ready datasets with standardized annotations.
• Secure funding opportunities through joint grant applications.

Interested in Partnering?

If you represent a research consortium or database provider, reach out to explore data-sharing agreements.

Contact: info@neurodiagnoses.com