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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.
	1	+== **Overview** ==
2	2
3		-**Neuromarker: Generalized Biomarker Ontology**
	3	+Neurodiagnoses develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility.**
4	4
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.
	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).
6	6
7		-**Core Biomarker Categories**
	11	+By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
8	8
9		-Within the Neurodiagnoses AI framework, biomarkers are categorized as follows:
	13	+----
10	10
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
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
	15	+== **Data Integration & External Databases** ==
20	20
21		-**Integrating External Databases into Neurodiagnoses**
	17	+=== **How to Use External Databases in Neurodiagnoses** ===
22	22
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:
	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.
24	24
25		-1. (((
26		-**Register for Access**
	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]]
27	27
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**
	24	+=== **Register for Access** ===
34	34
35		-* Download datasets while adhering to database usage policies.
36		-* (((
37		-Ensure files meet Neurodiagnoses format requirements:
	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).**
38	38
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**:
	30	+=== **Download & Prepare Data** ===
47	47
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**
	32	+Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
57	57
58		-* (((
59		-**Option 1: Upload to EBRAINS Bucket**
	34	+**Supported File Formats**
60	60
61		-* Location: EBRAINS Neurodiagnoses Bucket
62		-* Ensure correct metadata tagging before submission.
63		-)))
64		-* (((
65		-**Option 2: Contribute via GitHub Repository**
	36	+* **Tabular Data**: .csv, .tsv
	37	+* **Neuroimaging Data**: .nii, .dcm
	38	+* **Genomic Data**: .fasta, .vcf
	39	+* **Clinical Metadata**: .json, .xml
66	66
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**
	41	+**Mandatory Fields for Integration**
74	74
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.
	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
79	79
80		-**Reference**: See docs/data_processing.md for detailed instructions.
81		-)))
	50	+=== **Upload Data to Neurodiagnoses** ===
82	82
83		-**AI-Driven Biomarker Categorization**
	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]]
84	84
85		-Neurodiagnoses employs advanced AI models for biomarker classification:
	55	+**For large datasets, please contact project administrators before uploading.**
86	86
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
	57	+=== **Integrate Data into AI Models** ===
91	91
92		-**Collaboration & Partnerships**
	59	+Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
	60	+Standardize data using **harmonization tools.**
	61	+Train AI models with **newly integrated datasets.**
93	93
94		-Neurodiagnoses actively seeks partnerships with data providers to:
	63	+**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
95	95
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.
	65	+----
99	99
100		-**Interested in Partnering?**
	67	+== **AI-Powered Annotation & Machine Learning Models** ==
101	101
102		-If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
	69	+Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
103	103
104		-**Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
	71	+=== **AI Model Categories** ===
105	105
106		-
	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
	79	+
	80	+**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
	81	+
	82	+----
	83	+
	84	+== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
	85	+
	86	+Neurodiagnoses generates **structured AI reports** for clinicians, combining:
	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!**

workflow neurodiagnoses.png

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