Wiki source code of Methodology

Version 17.1 by manuelmenendez on 2025/02/09 13:01

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15.1	1	== Overview ==
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17.1	3	Neurodiagnoses develops a tridimensional diagnostic framework for CNS diseases, incorporating AI-powered annotation tools to improve interpretability, standardization, and clinical utility.
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17.1	5	This methodology integrates multi-modal data, including:
	6	Genetic data (whole-genome sequencing, polygenic risk scores).
	7	Neuroimaging (MRI, PET, EEG, MEG).
	8	Neurophysiological data (EEG-based biomarkers, sleep actigraphy).
	9	CSF & Blood Biomarkers (Amyloid-beta, Tau, Neurofilament Light).
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17.1	11	By applying machine learning models, Neurodiagnoses generates structured, explainable diagnostic outputs to assist clinical decision-making and biomarker-driven patient stratification.
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17.1	15	== Data Integration & External Databases ==
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17.1	17	=== How to Use External Databases in Neurodiagnoses ===
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17.1	19	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.
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17.1	21	Potential Data Sources
	22	Reference: [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
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17.1	24	=== Register for Access ===
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17.1	26	Each external database requires individual registration and approval.
	27	✔️ Follow the official data access guidelines of each provider.
	28	✔️ Ensure compliance with ethical approvals and data-sharing agreements (DUAs).
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17.1	30	=== Download & Prepare Data ===
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17.1	32	Once access is granted, download datasets following compliance guidelines and format requirements for integration.
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17.1	34	Supported File Formats
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17.1	36	* Tabular Data: .csv, .tsv
	37	* Neuroimaging Data: .nii, .dcm
	38	* Genomic Data: .fasta, .vcf
	39	* Clinical Metadata: .json, .xml
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17.1	41	Mandatory Fields for Integration
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17.1	43	\|=Field Name\|=Description
	44	\|Subject ID\|Unique patient identifier
	45	\|Diagnosis\|Standardized disease classification
	46	\|Biomarkers\|CSF, plasma, or imaging biomarkers
	47	\|Genetic Data\|Whole-genome or exome sequencing
	48	\|Neuroimaging Metadata\|MRI/PET acquisition parameters
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17.1	50	=== Upload Data to Neurodiagnoses ===
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17.1	52	Option 1: Upload to EBRAINS Bucket → [[Neurodiagnoses Data Storage>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
	53	Option 2: Contribute via GitHub Repository → [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
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17.1	55	For large datasets, please contact project administrators before uploading.
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17.1	57	=== Integrate Data into AI Models ===
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17.1	59	Use Jupyter Notebooks on EBRAINS for data preprocessing.
	60	Standardize data using harmonization tools.
	61	Train AI models with newly integrated datasets.
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17.1	63	Reference: [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
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17.1	67	== AI-Powered Annotation & Machine Learning Models ==
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17.1	69	Neurodiagnoses applies advanced machine learning models to classify CNS diseases, extract features from biomarkers and neuroimaging, and provide AI-powered annotation.
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17.1	71	=== AI Model Categories ===
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17.1	73	\|=Model Type\|=Function\|=Example Algorithms
	74	\|Probabilistic Diagnosis\|Assigns probability scores to multiple CNS disorders.\|Random Forest, XGBoost, Bayesian Networks
	75	\|Tridimensional Diagnosis\|Classifies disorders based on Etiology, Biomarkers, and Neuroanatomical Correlations.\|CNNs, Transformers, Autoencoders
	76	\|Biomarker Prediction\|Predicts missing biomarker values using regression.\|KNN Imputation, Bayesian Estimation
	77	\|Neuroimaging Feature Extraction\|Extracts patterns from MRI, PET, EEG.\|CNNs, Graph Neural Networks
	78	\|Clinical Decision Support\|Generates AI-driven diagnostic reports.\|SHAP Explainability Tools
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17.1	80	Reference: [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
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17.1	84	== Clinical Decision Support & Tridimensional Diagnostic Framework ==
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17.1	86	Neurodiagnoses generates structured AI reports for clinicians, combining:
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17.1	88	Probabilistic Diagnosis: AI-generated ranking of potential diagnoses.
	89	Tridimensional Classification: Standardized diagnostic reports based on:
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17.1	91	1. Axis 1: Etiology → Genetic, Autoimmune, Prion, Toxic, Vascular.
	92	1. Axis 2: Molecular Markers → CSF, Neuroinflammation, EEG biomarkers.
	93	1. Axis 3: Neuroanatomoclinical Correlations → MRI atrophy, PET.
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17.1	95	Reference: [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
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17.1	99	== Data Security, Compliance & Federated Learning ==
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17.1	101	✔ Privacy-Preserving AI: Implements Federated Learning, ensuring that patient data never leaves local institutions.
	102	✔ Secure Data Access: Data remains stored in EBRAINS MIP servers using differential privacy techniques.
	103	✔ Ethical & GDPR Compliance: Data-sharing agreements must be signed before use.
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17.1	105	Reference: [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
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17.1	109	== Data Processing & Integration with Clinica.Run ==
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17.1	111	Neurodiagnoses now supports Clinica.Run, an open-source neuroimaging platform for multimodal data processing.
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17.1	113	=== How It Works ===
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17.1	115	✔ Neuroimaging Preprocessing: MRI, PET, EEG data is preprocessed using Clinica.Run pipelines.
	116	✔ Automated Biomarker Extraction: Extracts volumetric, metabolic, and functional biomarkers.
	117	✔ Data Security & Compliance: Clinica.Run is GDPR & HIPAA-compliant.
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17.1	119	=== Implementation Steps ===
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17.1	121	1. Install Clinica.Run dependencies.
	122	1. Configure Clinica.Run pipeline in clinica_run_config.json.
	123	1. Run biomarker extraction pipelines for AI-based diagnostics.
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17.1	125	Reference: [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
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17.1	129	== Collaborative Development & Research ==
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17.1	131	We Use GitHub to Develop AI Models & Store Research Data
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17.1	133	* GitHub Repository: AI model training scripts.
	134	* GitHub Issues: Tracks ongoing research questions.
	135	* GitHub Wiki: Project documentation & user guides.
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17.1	137	We Use EBRAINS for Data & Collaboration
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17.1	139	* EBRAINS Buckets: Large-scale neuroimaging and biomarker storage.
	140	* EBRAINS Jupyter Notebooks: Cloud-based AI model execution.
	141	* EBRAINS Wiki: Research documentation and updates.
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17.1	143	Join the Project Forum: [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
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17.1	147	For Additional Documentation:
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17.1	149	* GitHub Repository: [[Neurodiagnoses AI Models>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
	150	* EBRAINS Wiki: [[Neurodiagnoses Research Collaboration>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
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17.1	154	Neurodiagnoses is Open for Contributions – Join Us Today!

Wiki source code of Methodology

Neurodiagnoses