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--**# Neurodiagnoses AI: Multimodal AI for Neurodiagnostic Predictions**
++== **Overview** ==
--## **Project Overview**
--Neurodiagnoses AI implements AI-driven diagnostic and prognostic models for central nervous system (CNS) disorders, adapting the Florey Dementia Index (FDI) methodology to a broader set of neurological conditions. The approach integrates **multimodal data sources** (EEG, neuroimaging, biomarkers, and genetics) and employs **machine learning models** to provide **explainable, real-time diagnostic insights**.##
++Neurodiagnoses develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility.**
--## **How to Use External Databases in Neurodiagnoses**
--To enhance diagnostic accuracy, Neurodiagnoses integrates data from multiple biomedical and neurological research databases. Researchers can follow these steps to access, prepare, and integrate data into the Neurodiagnoses framework.##
++This methodology integrates **multi-modal data**, including:
++**Genetic data** (whole-genome sequencing, polygenic risk scores).
++**Neuroimaging** (MRI, PET, EEG, MEG).
++**Neurophysiological data** (EEG-based biomarkers, sleep actigraphy).
++**CSF & Blood Biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
--### **Potential Data Sources**
--Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases. ##
++By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
--**Reference: List of Potential Databases**
--- **ADNI**: Alzheimer's Disease data ([ADNI](https://adni.loni.usc.edu))
--- **PPMI**: Parkinson’s Disease Imaging and biospecimens ([PPMI](https://www.ppmi-info.org))
--- **GP2**: Whole-genome sequencing for PD ([GP2](https://gp2.org))
--- **Enroll-HD**: Huntington’s Disease Clinical and genetic data ([Enroll-HD](https://www.enroll-hd.org))
--- **GAAIN**: Multi-source Alzheimer’s data aggregation ([GAAIN](https://gaain.org))
--- **UK Biobank**: Population-wide genetic, imaging, and health records ([UK Biobank](https://www.ukbiobank.ac.uk))
--- **DPUK**: Dementia and Aging data ([DPUK](https://www.dementiasplatform.uk))
--- **PRION Registry**: Prion Diseases clinical and genetic data ([PRION Registry](https://prionregistry.org))
--- **DECIPHER**: Rare genetic disorder genomic variants ([DECIPHER](https://decipher.sanger.ac.uk))
++----
--### **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.##
++== **Data Integration & External Databases** ==
--### **2. Download & Prepare Data**
--- Download datasets while adhering to database usage policies.
--- Ensure files meet **Neurodiagnoses format requirements**:
--  - **Tabular Data**: `.csv`, `.tsv`
--  - **Neuroimaging Data**: `.nii`, `.dcm`
--  - **Genomic Data**: `.fasta`, `.vcf`
--  - **Clinical Metadata**: `.json`, `.xml`##
++=== **How to Use External Databases in Neurodiagnoses** ===
--- **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
++Neurodiagnoses integrates data from multiple **biomedical and neurological research databases**. Researchers can follow these steps to **access, prepare, and integrate** data into the Neurodiagnoses framework.
--### **3. Upload Data to Neurodiagnoses**
--**Option 1: Upload to EBRAINS Bucket**
--- Location: **EBRAINS Neurodiagnoses Bucket**
--- Ensure correct **metadata tagging** before submission.##
++**Potential Data Sources**
++**Reference:** [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
-- **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.
++=== **Register for Access** ===
--### **4. Integrate Data into AI Models**
--- Open **Jupyter Notebooks** on EBRAINS to run **preprocessing scripts**.
--- Standardize **neuroimaging and biomarker formats** using harmonization tools.
--- Use **machine learning models** to handle missing data and feature extraction.
--- Train AI models with **newly integrated patient cohorts**.##
++Each **external database** requires **individual registration** and approval.
++✔️ Follow the official **data access guidelines** of each provider.
++✔️ Ensure compliance with **ethical approvals** and **data-sharing agreements (DUAs).**
--**Reference**: See `docs/data_processing.md` for detailed instructions.
++=== **Download & Prepare Data** ===
--## **Collaboration & Partnerships**##
--# **Partnering with Data Providers**
--Neurodiagnoses seeks partnerships with data repositories 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.
++Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
--**Interested in Partnering?**
--- If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
--- **Contact**: info@neurodiagnoses.com
++**Supported File Formats**
--## **Final Notes**
--Neurodiagnoses continuously expands its data ecosystem to support AI-driven clinical decision-making. Researchers and institutions are encouraged to contribute **new datasets and methodologies**.##
++* **Tabular Data**: .csv, .tsv
++* **Neuroimaging Data**: .nii, .dcm
++* **Genomic Data**: .fasta, .vcf
++* **Clinical Metadata**: .json, .xml
--For additional technical documentation:
--- **GitHub Repository**: [Neurodiagnoses GitHub](https://github.com/neurodiagnoses)
--- **EBRAINS Collaboration Page**: [EBRAINS Neurodiagnoses](https://ebrains.eu/collabs/neurodiagnoses)
++**Mandatory Fields for Integration**
--If you experience issues integrating data, **open a GitHub Issue** or consult the **EBRAINS Neurodiagnoses Forum**.
++|=**Field Name**|=**Description**
++|**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
--== **How to Use External Databases in Neurodiagnoses** ==
++=== **Upload Data to Neurodiagnoses** ===
--To enhance the accuracy of our diagnostic models, Neurodiagnoses integrates data from multiple biomedical and neurological research databases. If you are a researcher, follow these steps to access, prepare, and integrate data into the Neurodiagnoses framework.
++**Option 1:** Upload to **EBRAINS Bucket** → [[Neurodiagnoses Data Storage>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
++**Option 2:** Contribute via **GitHub Repository** → [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
--=== **Potential Data Sources** ===
++**For large datasets, please contact project administrators before uploading.**
--Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
++=== **Integrate Data into AI Models** ===
--* Reference: [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
++Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
++Standardize data using **harmonization tools.**
++Train AI models with **newly integrated datasets.**
--=== **1. Register for Access** ===
++**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
--Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
++----
--* Ensure that you have completed all ethical approvals and data access agreements before integrating datasets into Neurodiagnoses.
--* Some repositories require a Data Usage Agreement (DUA) before downloading sensitive medical data.
++== **AI-Powered Annotation & Machine Learning Models** ==
--=== **2. Download & Prepare Data** ===
++Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
--Once access is granted, download datasets while complying with data usage policies. Ensure that the files meet Neurodiagnoses’ format requirements for smooth integration.
++=== **AI Model Categories** ===
--==== **Supported File Formats** ====
++|=**Model Type**|=**Function**|=**Example Algorithms**
++|**Probabilistic Diagnosis**|Assigns probability scores to multiple CNS disorders.|Random Forest, XGBoost, Bayesian Networks
++|**Tridimensional Diagnosis**|Classifies disorders based on Etiology, Biomarkers, and Neuroanatomical Correlations.|CNNs, Transformers, Autoencoders
++|**Biomarker Prediction**|Predicts missing biomarker values using regression.|KNN Imputation, Bayesian Estimation
++|**Neuroimaging Feature Extraction**|Extracts patterns from MRI, PET, EEG.|CNNs, Graph Neural Networks
++|**Clinical Decision Support**|Generates AI-driven diagnostic reports.|SHAP Explainability Tools
--* Tabular Data: .csv, .tsv
--* Neuroimaging Data: .nii, .dcm
--* Genomic Data: .fasta, .vcf
--* Clinical Metadata: .json, .xml
++**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
--==== **Mandatory Fields for Integration** ====
++----
--|=Field Name|=Description
--|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
++== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
--=== **3. Upload Data to Neurodiagnoses** ===
++Neurodiagnoses generates **structured AI reports** for clinicians, combining:
--Once preprocessed, data can be uploaded to EBRAINS or GitHub.
++**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
++**Tridimensional Classification:** Standardized diagnostic reports based on:
--* (((
--**Option 1: Upload to EBRAINS Bucket**
++1. **Axis 1:** **Etiology** → Genetic, Autoimmune, Prion, Toxic, Vascular.
++1. **Axis 2:** **Molecular Markers** → CSF, Neuroinflammation, EEG biomarkers.
++1. **Axis 3:** **Neuroanatomoclinical Correlations** → MRI atrophy, PET.
--* Location: [[EBRAINS Neurodiagnoses Bucket>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
--* Ensure correct metadata tagging before submission.
--)))
--* (((
--**Option 2: Contribute via GitHub Repository**
++**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
--* Location: [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
--* Create a new folder under /data/ and include dataset description.
--)))
++----
--//Note: For large datasets, please contact the project administrators before uploading.//
++== **Data Security, Compliance & Federated Learning** ==
--=== **4. Integrate Data into AI Models** ===
++✔ **Privacy-Preserving AI**: Implements **Federated Learning**, ensuring that patient data **never leaves** local institutions.
++✔ **Secure Data Access**: Data remains **stored in EBRAINS MIP servers** using **differential privacy techniques.**
++✔ **Ethical & GDPR Compliance**: Data-sharing agreements **must be signed** before use.
--Once uploaded, datasets must be harmonized and formatted before AI model training.
++**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
--==== **Steps for Data Integration** ====
--
--* Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
--* Standardize neuroimaging and biomarker formats using harmonization tools.
--* Use machine learning models to handle missing data and feature extraction.
--* Train AI models with newly integrated patient cohorts.
--* Reference: [[Detailed instructions can be found in docs/data_processing.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]].
--
  ----
--== **Database Sources Table** ==
++== **Data Processing & Integration with Clinica.Run** ==
--=== **Where to Insert This** ===
++Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
--* GitHub: [[docs/data_sources.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_sources.md]]
--* EBRAINS Wiki: Collabs/neurodiagnoses/Data Sources
++=== **How It Works** ===
--=== **Key Databases for Neurodiagnoses** ===
++✔ **Neuroimaging Preprocessing**: MRI, PET, EEG data is preprocessed using **Clinica.Run pipelines.**
++✔ **Automated Biomarker Extraction**: Extracts volumetric, metabolic, and functional biomarkers.
++✔ **Data Security & Compliance**: Clinica.Run is **GDPR & HIPAA-compliant.**
--|=Database|=Focus Area|=Data Type|=Access Link
--|ADNI|Alzheimer's Disease|MRI, PET, CSF, cognitive tests|ADNI
--|PPMI|Parkinson’s Disease|Imaging, biospecimens|[[PPMI>>url:https://www.ppmi-info.org/]]
--|GP2|Genetic Data for PD|Whole-genome sequencing|[[GP2>>url:https://gp2.org/]]
--|Enroll-HD|Huntington’s Disease|Clinical, genetic, imaging|[[Enroll-HD>>url:https://enroll-hd.org/]]
--|GAAIN|Alzheimer's & Cognitive Decline|Multi-source data aggregation|[[GAAIN>>url:https://www.gaain.org/]]
--|UK Biobank|Population-wide studies|Genetic, imaging, health records|[[UK Biobank>>url:https://www.ukbiobank.ac.uk/]]
--|DPUK|Dementia & Aging|Imaging, genetics, lifestyle factors|[[DPUK>>url:https://www.dementiasplatform.uk/]]
--|PRION Registry|Prion Diseases|Clinical and genetic data|[[PRION Registry>>url:https://www.prionalliance.org/]]
--|DECIPHER|Rare Genetic Disorders|Genomic variants|DECIPHER
++=== **Implementation Steps** ===
--If you know a relevant dataset, submit a proposal in [[GitHub Issues>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]].
++1. Install **Clinica.Run** dependencies.
++1. Configure **Clinica.Run pipeline** in clinica_run_config.json.
++1. Run **biomarker extraction pipelines** for AI-based diagnostics.
++**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
++
  ----
--== **Collaboration & Partnerships** ==
++== **Collaborative Development & Research** ==
--=== **Where to Insert This** ===
++**We Use GitHub to Develop AI Models & Store Research Data**
--* GitHub: [[docs/collaboration.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/collaboration.md]]
--* EBRAINS Wiki: Collabs/neurodiagnoses/Collaborations
++* **GitHub Repository:** AI model training scripts.
++* **GitHub Issues:** Tracks ongoing research questions.
++* **GitHub Wiki:** Project documentation & user guides.
--=== **Partnering with Data Providers** ===
++**We Use EBRAINS for Data & Collaboration**
--Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
++* **EBRAINS Buckets:** Large-scale neuroimaging and biomarker storage.
++* **EBRAINS Jupyter Notebooks:** Cloud-based AI model execution.
++* **EBRAINS Wiki:** Research documentation and updates.
--* Enable direct API-based data integration for real-time processing.
--* Co-develop harmonized AI-ready datasets with standardized annotations.
--* Secure funding opportunities through joint grant applications.
++**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
--=== **Interested in Partnering?** ===
++----
--If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
++**For Additional Documentation:**
--* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
++* **GitHub Repository:** [[Neurodiagnoses AI Models>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
++* **EBRAINS Wiki:** [[Neurodiagnoses Research Collaboration>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
  ----
--== **Final Notes** ==
--
--Neurodiagnoses continuously expands its data ecosystem to support AI-driven clinical decision-making. Researchers and institutions are encouraged to contribute new datasets and methodologies.
--
--For additional technical documentation:
--
--* [[GitHub Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
--* [[EBRAINS Collaboration Page>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
--
--If you experience issues integrating data, open a [[GitHub Issue>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]] or consult the EBRAINS Neurodiagnoses Forum.
++**Neurodiagnoses is Open for Contributions – Join Us Today!**