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1		-==== **Overview** ====
	1	+== **Overview** ==
2	2
3		-This project develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility**. The methodology integrates **multi-modal data**, including **genetic, neuroimaging, neurophysiological, and biomarker datasets**, and applies **machine learning models** to generate **structured, explainable diagnostic outputs**.
	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		-=== **Workflow** ===
	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		-1. (((
8		-**We Use GitHub to [[Store and develop AI models, scripts, and annotation pipelines.>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]**
	11	+By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
9	9
10		-* Create a **GitHub repository** for AI scripts and models.
11		-* Use **GitHub Projects** to manage research milestones.
12		-)))
13		-1. (((
14		-**We Use EBRAINS for Data & Collaboration**
15		-
16		-* Store **biomarker and neuroimaging data** in **EBRAINS Buckets**.
17		-* Run **Jupyter Notebooks** in **EBRAINS Lab** to test AI models.
18		-* Use **EBRAINS Wiki** for structured documentation and research discussion.
19		-)))
20		-
21	21	----
22	22
23		-=== **1. Data Integration** ===
	15	+== **Data Integration & External Databases** ==
24	24
25		-== Overview ==
	17	+=== **How to Use External Databases in Neurodiagnoses** ===
26	26
	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.
27	27
28		-Neurodiagnoses integrates clinical data via the **EBRAINS Medical Informatics Platform (MIP)**. MIP federates decentralized clinical data, allowing Neurodiagnoses to securely access and process sensitive information for AI-based diagnostics.
	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]]
29	29
30		-== How It Works ==
	24	+=== **Register for Access** ===
31	31
	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).**
32	32
33		-1. (((
34		-**Authentication & API Access:**
	30	+=== **Download & Prepare Data** ===
35	35
36		-* Users must have an **EBRAINS account**.
37		-* Neurodiagnoses uses **secure API endpoints** to fetch clinical data (e.g., from the **Federation for Dementia**).
38		-)))
39		-1. (((
40		-**Data Mapping & Harmonization:**
	32	+Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
41	41
42		-* Retrieved data is **normalized** and converted to standard formats (.csv, .json).
43		-* Data from **multiple sources** is harmonized to ensure consistency for AI processing.
44		-)))
45		-1. (((
46		-**Security & Compliance:**
	34	+**Supported File Formats**
47	47
48		-* All data access is **logged and monitored**.
49		-* Data remains on **MIP servers** using **federated learning techniques** when possible.
50		-* Access is granted only after signing a **Data Usage Agreement (DUA)**.
51		-)))
	36	+* **Tabular Data**: .csv, .tsv
	37	+* **Neuroimaging Data**: .nii, .dcm
	38	+* **Genomic Data**: .fasta, .vcf
	39	+* **Clinical Metadata**: .json, .xml
52	52
53		-== Implementation Steps ==
	41	+**Mandatory Fields for Integration**
54	54
	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
55	55
56		-1. Clone the repository.
57		-1. Configure your **EBRAINS API credentials** in mip_integration.py.
58		-1. Run the script to **download and harmonize clinical data**.
59		-1. Process the data for **AI model training**.
	50	+=== **Upload Data to Neurodiagnoses** ===
60	60
61		-For more detailed instructions, please refer to the **[[MIP Documentation>>url:https://mip.ebrains.eu/]]**.
	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]]
62	62
63		-----
	55	+**For large datasets, please contact project administrators before uploading.**
64	64
65		-= Data Processing & Integration with Clinica.Run =
	57	+=== **Integrate Data into AI Models** ===
66	66
	59	+Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
	60	+Standardize data using **harmonization tools.**
	61	+Train AI models with **newly integrated datasets.**
67	67
68		-== Overview ==
	63	+**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
69	69
	65	+----
70	70
71		-Neurodiagnoses now supports **Clinica.Run**, an open-source neuroimaging platform designed for **multimodal data processing and reproducible neuroscience workflows**.
	67	+== **AI-Powered Annotation & Machine Learning Models** ==
72	72
73		-== How It Works ==
	69	+Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
74	74
	71	+=== **AI Model Categories** ===
75	75
76		-1. (((
77		-**Neuroimaging Preprocessing:**
	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
78	78
79		-* MRI, PET, EEG data is preprocessed using **Clinica.Run pipelines**.
80		-* Supports **longitudinal and cross-sectional analyses**.
81		-)))
82		-1. (((
83		-**Automated Biomarker Extraction:**
	80	+**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
84	84
85		-* Standardized extraction of **volumetric, metabolic, and functional biomarkers**.
86		-* Integration with machine learning models in Neurodiagnoses.
87		-)))
88		-1. (((
89		-**Data Security & Compliance:**
90		-
91		-* Clinica.Run operates in **compliance with GDPR and HIPAA**.
92		-* Neuroimaging data remains **within the original storage environment**.
93		-)))
94		-
95		-== Implementation Steps ==
96		-
97		-
98		-1. Install **Clinica.Run** dependencies.
99		-1. Configure your **Clinica.Run pipeline** in clinica_run_config.json.
100		-1. Run the pipeline for **preprocessing and biomarker extraction**.
101		-1. Use processed neuroimaging data for **AI-driven diagnostics** in Neurodiagnoses.
102		-
103		-For further information, refer to **[[Clinica.Run Documentation>>url:https://clinica.run/]]**.
104		-
105		-==== ====
106		-
107		-==== **Data Sources** ====
108		-
109		-[[List of potential sources of databases>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
110		-
111		-**Biomedical Ontologies & Databases:**
112		-
113		-* **Human Phenotype Ontology (HPO)** for symptom annotation.
114		-* **Gene Ontology (GO)** for molecular and cellular processes.
115		-
116		-**Dimensionality Reduction and Interpretability:**
117		-
118		-* **Evaluate interpretability** using metrics like the **Area Under the Interpretability Curve (AUIC)**.
119		-* **Leverage [[DEIBO>>https://github.com/Mellandd/DEIBO]] (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
120		-
121		-**Neuroimaging & EEG/MEG Data:**
122		-
123		-* **MRI volumetric measures** for brain atrophy tracking.
124		-* **EEG functional connectivity patterns** (AI-Mind).
125		-
126		-**Clinical & Biomarker Data:**
127		-
128		-* **CSF biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
129		-* **Sleep monitoring and actigraphy data** (ADIS).
130		-
131		-**Federated Learning Integration:**
132		-
133		-* **Secure multi-center data harmonization** (PROMINENT).
134		-
135	135	----
136	136
137		-==== **Annotation System for Multi-Modal Data** ====
	84	+== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
138	138
139		-To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
	86	+Neurodiagnoses generates **structured AI reports** for clinicians, combining:
140	140
141		-* **Assign standardized metadata tags** to diagnostic features.
142		-* **Provide contextual explanations** for AI-based classifications.
143		-* **Track temporal disease progression annotations** to identify long-term trends.
	88	+**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
	89	+**Tridimensional Classification:** Standardized diagnostic reports based on:
144	144
145		-----
	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.
146	146
147		-=== **2. AI-Based Analysis** ===
	95	+**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
148	148
149		-==== **Machine Learning & Deep Learning Models** ====
150		-
151		-**Risk Prediction Models:**
152		-
153		-* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
154		-
155		-**Biomarker Classification & Probabilistic Imputation:**
156		-
157		-* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
158		-
159		-**Neuroimaging Feature Extraction:**
160		-
161		-* **MRI & EEG data** annotated with **neuroanatomical feature labels**.
162		-
163		-==== **AI-Powered Annotation System** ====
164		-
165		-* Uses **SHAP-based interpretability tools** to explain model decisions.
166		-* Generates **automated clinical annotations** in structured reports.
167		-* Links findings to **standardized medical ontologies** (e.g., **SNOMED, HPO**).
168		-
169	169	----
170	170
171		-=== **3. Diagnostic Framework & Clinical Decision Support** ===
	99	+== **Data Security, Compliance & Federated Learning** ==
172	172
173		-==== **Tridimensional Diagnostic Axes** ====
	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.
174	174
175		-**Axis 1: Etiology (Pathogenic Mechanisms)**
	105	+**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
176	176
177		-* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
178		-* **AI-assisted annotation** provides **causal interpretations** for clinical use.
179		-
180		-**Axis 2: Molecular Markers & Biomarkers**
181		-
182		-* **Integration of CSF, blood, and neuroimaging biomarkers**.
183		-* **Structured annotation** highlights **biological pathways linked to diagnosis**.
184		-
185		-**Axis 3: Neuroanatomoclinical Correlations**
186		-
187		-* **MRI and EEG data** provide anatomical and functional insights.
188		-* **AI-generated progression maps** annotate **brain structure-function relationships**.
189		-
190	190	----
191	191
192		-=== **4. Computational Workflow & Annotation Pipelines** ===
	109	+== **Data Processing & Integration with Clinica.Run** ==
193	193
194		-==== **Data Processing Steps** ====
	111	+Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
195	195
196		-**Data Ingestion:**
	113	+=== **How It Works** ===
197	197
198		-* **Harmonized datasets** stored in **EBRAINS Bucket**.
199		-* **Preprocessing pipelines** clean and standardize data.
	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.**
200	200
201		-**Feature Engineering:**
	119	+=== **Implementation Steps** ===
202	202
203		-* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
	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.
204	204
205		-**AI-Generated Annotations:**
	125	+**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
206	206
207		-* **Automated tagging** of diagnostic features in **structured reports**.
208		-* **Explainability modules (SHAP, LIME)** ensure transparency in predictions.
209		-
210		-**Clinical Decision Support Integration:**
211		-
212		-* **AI-annotated findings** fed into **interactive dashboards**.
213		-* **Clinicians can adjust, validate, and modify annotations**.
214		-
215	215	----
216	216
217		-=== **5. Validation & Real-World Testing** ===
	129	+== **Collaborative Development & Research** ==
218	218
219		-==== **Prospective Clinical Study** ====
	131	+**We Use GitHub to Develop AI Models & Store Research Data**
220	220
221		-* **Multi-center validation** of AI-based **annotations & risk stratifications**.
222		-* **Benchmarking against clinician-based diagnoses**.
223		-* **Real-world testing** of AI-powered **structured reporting**.
	133	+* **GitHub Repository:** AI model training scripts.
	134	+* **GitHub Issues:** Tracks ongoing research questions.
	135	+* **GitHub Wiki:** Project documentation & user guides.
224	224
225		-==== **Quality Assurance & Explainability** ====
	137	+**We Use EBRAINS for Data & Collaboration**
226	226
227		-* **Annotations linked to structured knowledge graphs** for improved transparency.
228		-* **Interactive annotation editor** allows clinicians to validate AI outputs.
	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.
229	229
230		-----
	143	+**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
231	231
232		-=== **6. Collaborative Development** ===
233		-
234		-The project is **open to contributions** from **researchers, clinicians, and developers**.
235		-
236		-**Key tools include:**
237		-
238		-* **Jupyter Notebooks**: For data analysis and pipeline development.
239		-** Example: **probabilistic imputation**
240		-* **Wiki Pages**: For documenting methods and results.
241		-* **Drive and Bucket**: For sharing code, data, and outputs.
242		-* **Collaboration with related projects**:
243		-** Example: **Beyond the hype: AI in dementia – from early risk detection to disease treatment**
244		-
245	245	----
246	246
247		-=== **7. Tools and Technologies** ===
	147	+**For Additional Documentation:**
248	248
249		-==== **Programming Languages:** ====
	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/]]
250	250
251		-* **Python** for AI and data processing.
252		-
253		-==== **Frameworks:** ====
254		-
255		-* **TensorFlow** and **PyTorch** for machine learning.
256		-* **Flask** or **FastAPI** for backend services.
257		-
258		-==== **Visualization:** ====
259		-
260		-* **Plotly** and **Matplotlib** for interactive and static visualizations.
261		-
262		-==== **EBRAINS Services:** ====
263		-
264		-* **Collaboratory Lab** for running Notebooks.
265		-* **Buckets** for storing large datasets.
266		-
267	267	----
268	268
269		-=== **Why This Matters** ===
270		-
271		-* The annotation system ensures that AI-generated insights are structured, interpretable, and clinically meaningful.
272		-* It enables real-time tracking of disease progression across the three diagnostic axes.
273		-* It facilitates integration with electronic health records and decision-support tools, improving AI adoption in clinical workflows.
	154	+**Neurodiagnoses is Open for Contributions – Join Us Today!**