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1		-Here is the updated **Methodology** section for the EBRAINS Wiki, incorporating the **Generalized Neuro Biomarker Ontology Categorization (Neuromarker)** for **biomarker classification across all neurodegenerative diseases**.
	1	+== **Overview** ==
2	2
	3	+Neurodiagnoses develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility.**
	4	+
	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).
	10	+
	11	+By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
	12	+
3	3	----
4	4
5		-== **Neurodiagnoses AI: Multimodal AI for Neurodiagnostic Predictions** ==
	15	+== **Data Integration & External Databases** ==
6	6
7		-=== **Project Overview** ===
	17	+=== **How to Use External Databases in Neurodiagnoses** ===
8	8
9		-Neurodiagnoses AI implements **AI-driven diagnostic and prognostic models** for central nervous system (CNS) disorders, expanding 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**. This framework now incorporates **Neuromarker**, a **generalized biomarker ontology** that categorizes biomarkers across neurodegenerative diseases, enabling **standardized, cross-disease AI training**.
	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.
10	10
11		-== **Neuromarker: Generalized Biomarker Ontology** ==
	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]]
12	12
13		-Neuromarker extends the **Common Alzheimer’s Disease Research Ontology (CADRO)** into a **cross-disease biomarker categorization framework** applicable to all neurodegenerative diseases (NDDs). It allows for **standardized classification, AI-based feature extraction, and multimodal integration**.
	24	+=== **Register for Access** ===
14	14
15		-=== **Core Biomarker Categories** ===
	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).**
16	16
17		-The following ontology is used within **Neurodiagnoses AI** for biomarker categorization:
	30	+=== **Download & Prepare Data** ===
18	18
19		-|=**Category**|=**Description**
20		-|**Molecular Biomarkers**|Omics-based markers (genomic, transcriptomic, proteomic, metabolomic, lipidomic)
21		-|**Neuroimaging Biomarkers**|Structural (MRI, CT), Functional (fMRI, PET), Molecular Imaging (tau, amyloid, α-synuclein)
22		-|**Fluid Biomarkers**|CSF, plasma, blood-based markers for tau, amyloid, α-synuclein, TDP-43, GFAP, NfL
23		-|**Neurophysiological Biomarkers**|EEG, MEG, evoked potentials (ERP), sleep-related markers
24		-|**Digital Biomarkers**|Gait analysis, cognitive/speech biomarkers, wearables data, EHR-based markers
25		-|**Clinical Phenotypic Markers**|Standardized clinical scores (MMSE, MoCA, CDR, UPDRS, ALSFRS, UHDRS)
26		-|**Genetic Biomarkers**|Risk alleles (APOE, LRRK2, MAPT, C9orf72, PRNP) and polygenic risk scores
27		-|**Environmental & Lifestyle Factors**|Toxins, infections, diet, microbiome, comorbidities
	32	+Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
28	28
29		-----
	34	+**Supported File Formats**
30	30
31		-== **How to Use External Databases in Neurodiagnoses** ==
	36	+* **Tabular Data**: .csv, .tsv
	37	+* **Neuroimaging Data**: .nii, .dcm
	38	+* **Genomic Data**: .fasta, .vcf
	39	+* **Clinical Metadata**: .json, .xml
32	32
33		-To enhance diagnostic accuracy, Neurodiagnoses AI integrates data from **multiple biomedical and neurological research databases**. Researchers can follow these steps to access, prepare, and integrate data into the Neurodiagnoses framework.
	41	+**Mandatory Fields for Integration**
34	34
35		-=== **Potential Data Sources** ===
	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
36	36
37		-Neurodiagnoses maintains an **updated list** of biomedical datasets relevant to neurodegenerative diseases:
	50	+=== **Upload Data to Neurodiagnoses** ===
38	38
39		-* **ADNI**: Alzheimer's Disease Imaging & Biomarkers → [[ADNI>>url:https://adni.loni.usc.edu/]]
40		-* **PPMI**: Parkinson’s Disease Imaging & Biospecimens → [[PPMI>>url:https://www.ppmi-info.org/]]
41		-* **GP2**: Whole-Genome Sequencing for PD → [[GP2>>url:https://gp2.org/]]
42		-* **Enroll-HD**: Huntington’s Disease Clinical & Genetic Data → [[Enroll-HD>>url:https://www.enroll-hd.org/]]
43		-* **GAAIN**: Multi-Source Alzheimer’s Data Aggregation → [[GAAIN>>url:https://gaain.org/]]
44		-* **UK Biobank**: Population-Wide Genetic, Imaging & Health Records → [[UK Biobank>>url:https://www.ukbiobank.ac.uk/]]
45		-* **DPUK**: Dementia & Aging Data → [[DPUK>>url:https://www.dementiasplatform.uk/]]
46		-* **PRION Registry**: Prion Diseases Clinical & Genetic Data → [[PRION Registry>>url:https://prionregistry.org/]]
47		-* **DECIPHER**: Rare Genetic Disorder Genomic Variants → [[DECIPHER>>url:https://decipher.sanger.ac.uk/]]
	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]]
48	48
49		-----
	55	+**For large datasets, please contact project administrators before uploading.**
50	50
51		-== **1. Register for Access** ==
	57	+=== **Integrate Data into AI Models** ===
52	52
53		-* Each external database requires **individual registration and access approval**.
54		-* Ensure compliance with **ethical approvals and data usage agreements** before integrating datasets into Neurodiagnoses.
55		-* Some repositories may require a **Data Usage Agreement (DUA)** for sensitive medical data.
	59	+Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
	60	+Standardize data using **harmonization tools.**
	61	+Train AI models with **newly integrated datasets.**
56	56
	63	+**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
	64	+
57	57	----
58	58
59		-== **2. Download & Prepare Data** ==
	67	+== **AI-Powered Annotation & Machine Learning Models** ==
60	60
61		-* Download datasets while adhering to **database usage policies**.
62		-* Ensure files meet **Neurodiagnoses format requirements**:
	69	+Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
63	63
64		-|=**Data Type**|=**Accepted Formats**
65		-|**Tabular Data**|.csv, .tsv
66		-|**Neuroimaging**|.nii, .dcm
67		-|**Genomic Data**|.fasta, .vcf
68		-|**Clinical Metadata**|.json, .xml
	71	+=== **AI Model Categories** ===
69	69
70		-* **Mandatory Fields for Integration**:
71		-** **Subject ID**: Unique patient identifier
72		-** **Diagnosis**: Standardized disease classification
73		-** **Biomarkers**: CSF, plasma, or imaging biomarkers
74		-** **Genetic Data**: Whole-genome or exome sequencing
75		-** **Neuroimaging Metadata**: MRI/PET acquisition parameters
	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
76	76
	80	+**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
	81	+
77	77	----
78	78
79		-== **3. Upload Data to Neurodiagnoses** ==
	84	+== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
80	80
81		-=== **Option 1: Upload to EBRAINS Bucket** ===
	86	+Neurodiagnoses generates **structured AI reports** for clinicians, combining:
82	82
83		-* Location: **EBRAINS Neurodiagnoses Bucket**
84		-* Ensure **correct metadata tagging** before submission.
	88	+**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
	89	+**Tridimensional Classification:** Standardized diagnostic reports based on:
85	85
86		-=== **Option 2: Contribute via GitHub Repository** ===
	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.
87	87
88		-* Location: **GitHub Data Repository**
89		-* Create a **new folder under /data/** and include a **dataset description**.
90		-* **For large datasets**, contact project administrators before uploading.
	95	+**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
91	91
92	92	----
93	93
94		-== **4. Integrate Data into AI Models** ==
	99	+== **Data Security, Compliance & Federated Learning** ==
95	95
96		-* Open **Jupyter Notebooks** on EBRAINS to run **preprocessing scripts**.
97		-* **Standardize neuroimaging and biomarker formats** using harmonization tools.
98		-* Use **machine learning models** to handle **missing data** and **feature extraction**.
99		-* Train AI models with **newly integrated patient cohorts**.
	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.
100	100
101		-**Reference**: See docs/data_processing.md for detailed instructions.
	105	+**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
102	102
103	103	----
104	104
105		-== **AI-Driven Biomarker Categorization** ==
	109	+== **Data Processing & Integration with Clinica.Run** ==
106	106
107		-Neurodiagnoses employs **AI models** for biomarker classification:
	111	+Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
108	108
109		-|=**Model Type**|=**Application**
110		-|**Graph Neural Networks (GNNs)**|Identify shared biomarker pathways across diseases
111		-|**Contrastive Learning**|Distinguish overlapping vs. unique biomarkers
112		-|**Multimodal Transformer Models**|Integrate imaging, omics, and clinical data
	113	+=== **How It Works** ===
113	113
114		-----
	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.**
115	115
116		-== **Collaboration & Partnerships** ==
	119	+=== **Implementation Steps** ===
117	117
118		-=== **Partnering with Data Providers** ===
	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.
119	119
120		-Neurodiagnoses seeks partnerships with data repositories to:
	125	+**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
121	121
122		-* Enable **API-based data integration** for real-time processing.
123		-* Co-develop **harmonized AI-ready datasets** with standardized annotations.
124		-* Secure **funding opportunities** through joint grant applications.
	127	+----
125	125
126		-**Interested in Partnering?**
	129	+== **Collaborative Development & Research** ==
127	127
128		-* If you represent a **research consortium or database provider**, reach out to explore **data-sharing agreements**.
129		-* **Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
	131	+**We Use GitHub to Develop AI Models & Store Research Data**
130	130
131		-----
	133	+* **GitHub Repository:** AI model training scripts.
	134	+* **GitHub Issues:** Tracks ongoing research questions.
	135	+* **GitHub Wiki:** Project documentation & user guides.
132	132
133		-== **Final Notes** ==
	137	+**We Use EBRAINS for Data & Collaboration**
134	134
135		-Neurodiagnoses continuously expands its **data ecosystem** to support **AI-driven clinical decision-making**. Researchers and institutions are encouraged to **contribute new datasets and methodologies**.
	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.
136	136
137		-**For additional technical documentation**:
	143	+**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
138	138
139		-* **GitHub Repository**: [[Neurodiagnoses GitHub>>url:https://github.com/neurodiagnoses]]
140		-* **EBRAINS Collaboration Page**: [[EBRAINS Neurodiagnoses>>url:https://ebrains.eu/collabs/neurodiagnoses]]
	145	+----
141	141
142		-**If you experience issues integrating data**, open a **GitHub Issue** or consult the **EBRAINS Neurodiagnoses Forum**.
	147	+**For Additional Documentation:**
143	143
	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/]]
	151	+
144	144	----
145	145
146		-This **updated methodology** now incorporates [[https:~~/~~/github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/biomarker_ontology>>https://Neuromarker]] for standardized biomarker classification, enabling **cross-disease AI training** across neurodegenerative disorders.
	154	+**Neurodiagnoses is Open for Contributions – Join Us Today!**