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1		-== **Overview** ==
	1	+**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.
2	2
3		-Neurodiagnoses develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility.**
	3	+**Neuromarker: Generalized Biomarker Ontology**
4	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).
	5	+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.
10	10
11		-By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
	7	+**Core Biomarker Categories**
12	12
13		-----
	9	+Within the Neurodiagnoses AI framework, biomarkers are categorized as follows:
14	14
15		-== **Data Integration & External Databases** ==
	11	+|=**Category**|=**Description**
	12	+|**Molecular Biomarkers**|Omics-based markers (genomic, transcriptomic, proteomic, metabolomic, lipidomic)
	13	+|**Neuroimaging Biomarkers**|Structural (MRI, CT), Functional (fMRI, PET), Molecular Imaging (tau, amyloid, α-synuclein)
	14	+|**Fluid Biomarkers**|CSF, plasma, blood-based markers for tau, amyloid, α-synuclein, TDP-43, GFAP, NfL, autoantiboides
	15	+|**Neurophysiological Biomarkers**|EEG, MEG, evoked potentials (ERP), sleep-related markers
	16	+|**Digital Biomarkers**|Gait analysis, cognitive/speech biomarkers, wearables data, EHR-based markers
	17	+|**Clinical Phenotypic Markers**|Standardized clinical scores (MMSE, MoCA, CDR, UPDRS, ALSFRS, UHDRS)
	18	+|**Genetic Biomarkers**|Risk alleles (APOE, LRRK2, MAPT, C9orf72, PRNP) and polygenic risk scores
	19	+|**Environmental & Lifestyle Factors**|Toxins, infections, diet, microbiome, comorbidities
16	16
17		-=== **How to Use External Databases in Neurodiagnoses** ===
	21	+**Integrating External Databases into Neurodiagnoses**
18	18
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.
	23	+To enhance diagnostic precision, Neurodiagnoses AI incorporates data from multiple biomedical and neurological research databases. Researchers can integrate external datasets by following these steps:
20	20
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]]
	25	+1. (((
	26	+**Register for Access**
23	23
24		-=== **Register for Access** ===
	28	+* Each external database requires individual registration and access approval.
	29	+* Ensure compliance with ethical approvals and data usage agreements before integrating datasets into Neurodiagnoses.
	30	+* Some repositories may require a Data Usage Agreement (DUA) for sensitive medical data.
	31	+)))
	32	+1. (((
	33	+**Download & Prepare Data**
25	25
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).**
	35	+* Download datasets while adhering to database usage policies.
	36	+* (((
	37	+Ensure files meet Neurodiagnoses format requirements:
29	29
30		-=== **Download & Prepare Data** ===
	39	+|=**Data Type**|=**Accepted Formats**
	40	+|**Tabular Data**|.csv, .tsv
	41	+|**Neuroimaging**|.nii, .dcm
	42	+|**Genomic Data**|.fasta, .vcf
	43	+|**Clinical Metadata**|.json, .xml
	44	+)))
	45	+* (((
	46	+**Mandatory Fields for Integration**:
31	31
32		-Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
	48	+* Subject ID: Unique patient identifier
	49	+* Diagnosis: Standardized disease classification
	50	+* Biomarkers: CSF, plasma, or imaging biomarkers
	51	+* Genetic Data: Whole-genome or exome sequencing
	52	+* Neuroimaging Metadata: MRI/PET acquisition parameters
	53	+)))
	54	+)))
	55	+1. (((
	56	+**Upload Data to Neurodiagnoses**
33	33
34		-**Supported File Formats**
	58	+* (((
	59	+**Option 1: Upload to EBRAINS Bucket**
35	35
36		-* **Tabular Data**: .csv, .tsv
37		-* **Neuroimaging Data**: .nii, .dcm
38		-* **Genomic Data**: .fasta, .vcf
39		-* **Clinical Metadata**: .json, .xml
	61	+* Location: EBRAINS Neurodiagnoses Bucket
	62	+* Ensure correct metadata tagging before submission.
	63	+)))
	64	+* (((
	65	+**Option 2: Contribute via GitHub Repository**
40	40
41		-**Mandatory Fields for Integration**
	67	+* Location: GitHub Data Repository
	68	+* Create a new folder under /data/ and include a dataset description.
	69	+* For large datasets, contact project administrators before uploading.
	70	+)))
	71	+)))
	72	+1. (((
	73	+**Integrate Data into AI Models**
42	42
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
	75	+* Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
	76	+* Standardize neuroimaging and biomarker formats using harmonization tools.
	77	+* Utilize machine learning models to handle missing data and feature extraction.
	78	+* Train AI models with newly integrated patient cohorts.
49	49
50		-=== **Upload Data to Neurodiagnoses** ===
	80	+**Reference**: See docs/data_processing.md for detailed instructions.
	81	+)))
51	51
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]]
	83	+**AI-Driven Biomarker Categorization**
54	54
55		-**For large datasets, please contact project administrators before uploading.**
	85	+Neurodiagnoses employs advanced AI models for biomarker classification:
56	56
57		-=== **Integrate Data into AI Models** ===
	87	+|=**Model Type**|=**Application**
	88	+|**Graph Neural Networks (GNNs)**|Identify shared biomarker pathways across diseases
	89	+|**Contrastive Learning**|Distinguish overlapping vs. unique biomarkers
	90	+|**Multimodal Transformer Models**|Integrate imaging, omics, and clinical data
58	58
59		-Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
60		-Standardize data using **harmonization tools.**
61		-Train AI models with **newly integrated datasets.**
	92	+**Collaboration & Partnerships**
62	62
63		-**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
	94	+Neurodiagnoses actively seeks partnerships with data providers to:
64	64
65		-----
	96	+* Enable API-based data integration for real-time processing.
	97	+* Co-develop harmonized AI-ready datasets with standardized annotations.
	98	+* Secure funding opportunities through joint grant applications.
66	66
67		-== **AI-Powered Annotation & Machine Learning Models** ==
	100	+**Interested in Partnering?**
68	68
69		-Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
	102	+If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
70	70
71		-=== **AI Model Categories** ===
	104	+**Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
72	72
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
	106	+**Final Notes**
79	79
80		-**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
	108	+Neurodiagnoses AI is committed to advancing the integration of artificial intelligence in neurodiagnostic processes. By continuously expanding our data ecosystem and incorporating standardized biomarker classifications through the Neuromarker ontology, we aim to enhance cross-disease AI training and improve diagnostic accuracy across neurodegenerative disorders.
81	81
82		-----
	110	+We encourage researchers and institutions to contribute new datasets and methodologies to further enrich this collaborative platform. Your participation is vital in driving innovation and fostering a deeper understanding of complex neurological conditions.
83	83
84		-== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
	112	+**For additional technical documentation and collaboration opportunities:**
85	85
86		-Neurodiagnoses generates **structured AI reports** for clinicians, combining:
	114	+* **GitHub Repository:** [[Neurodiagnoses GitHub>>url:https://github.com/neurodiagnoses]]
	115	+* **EBRAINS Collaboration Page:** [[EBRAINS Neurodiagnoses>>url:https://ebrains.eu/collabs/neurodiagnoses]]
87	87
88		-**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
89		-**Tridimensional Classification:** Standardized diagnostic reports based on:
90		-
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.
94		-
95		-**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
96		-
97		-----
98		-
99		-== **Data Security, Compliance & Federated Learning** ==
100		-
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.
104		-
105		-**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
106		-
107		-----
108		-
109		-== **Data Processing & Integration with Clinica.Run** ==
110		-
111		-Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
112		-
113		-=== **How It Works** ===
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.**
118		-
119		-=== **Implementation Steps** ===
120		-
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.
124		-
125		-**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
126		-
127		-----
128		-
129		-== **Collaborative Development & Research** ==
130		-
131		-**We Use GitHub to Develop AI Models & Store Research Data**
132		-
133		-* **GitHub Repository:** AI model training scripts.
134		-* **GitHub Issues:** Tracks ongoing research questions.
135		-* **GitHub Wiki:** Project documentation & user guides.
136		-
137		-**We Use EBRAINS for Data & Collaboration**
138		-
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.
142		-
143		-**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
144		-
145		-----
146		-
147		-**For Additional Documentation:**
148		-
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		-
152		-----
153		-
154		-**Neurodiagnoses is Open for Contributions – Join Us Today!**
	117	+If you encounter any issues during data integration or have suggestions for improvement, please open a GitHub Issue or consult the EBRAINS Neurodiagnoses Forum. Together, we can advance the field of neurodiagnostics and contribute to better patient outcomes.

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