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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. The methodology integrates multi-modal data, including genetic, neuroimaging, neurophysiological, and biomarker datasets, and applies machine learning models to generate structured, explainable diagnostic outputs.
4	4
5		-=== **Workflow** ===
6		-
7		-1. (((
8		-**We Use GitHub to [[Store and develop AI models, scripts, and annotation pipelines.>>https://github.com/users/manuelmenendezgonzalez/projects/1/views/1]]**
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** ===
	7	+== **How to Use External Databases in Neurodiagnoses** ==
24	24
25		-==== **Data Sources** ====
	9	+To enhance the accuracy of our diagnostic models, Neurodiagnoses integrates data from multiple biomedical and neurological research databases. If you are a researcher, follow these steps to access, prepare, and integrate data into the Neurodiagnoses framework.
26	26
27		-**Biomedical Ontologies & Databases:**
	11	+=== **Potential Data Sources** ===
28	28
29		-* **Human Phenotype Ontology (HPO)** for symptom annotation.
30		-* **Gene Ontology (GO)** for molecular and cellular processes.
	13	+Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
31	31
32		-**Dimensionality Reduction and Interpretability:**
	15	+* Reference: [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
33	33
34		-* **Evaluate interpretability** using metrics like the **Area Under the Interpretability Curve (AUIC)**.
35		-* **Leverage DEIBO (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
	17	+=== **1. Register for Access** ===
36	36
37		-**Neuroimaging & EEG/MEG Data:**
	19	+Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
38	38
39		-* **MRI volumetric measures** for brain atrophy tracking.
40		-* **EEG functional connectivity patterns** (AI-Mind).
	21	+* Ensure that you have completed all ethical approvals and data access agreements before integrating datasets into Neurodiagnoses.
	22	+* Some repositories require a Data Usage Agreement (DUA) before downloading sensitive medical data.
41	41
42		-**Clinical & Biomarker Data:**
	24	+=== **2. Download & Prepare Data** ===
43	43
44		-* **CSF biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
45		-* **Sleep monitoring and actigraphy data** (ADIS).
	26	+Once access is granted, download datasets while complying with data usage policies. Ensure that the files meet Neurodiagnoses’ format requirements for smooth integration.
46	46
47		-**Federated Learning Integration:**
	28	+==== **Supported File Formats** ====
48	48
49		-* **Secure multi-center data harmonization** (PROMINENT).
	30	+* Tabular Data: .csv, .tsv
	31	+* Neuroimaging Data: .nii, .dcm
	32	+* Genomic Data: .fasta, .vcf
	33	+* Clinical Metadata: .json, .xml
50	50
51		-----
	35	+==== **Mandatory Fields for Integration** ====
52	52
53		-==== **Annotation System for Multi-Modal Data** ====
	37	+|=Field Name|=Description
	38	+|Subject ID|Unique patient identifier
	39	+|Diagnosis|Standardized disease classification
	40	+|Biomarkers|CSF, plasma, or imaging biomarkers
	41	+|Genetic Data|Whole-genome or exome sequencing
	42	+|Neuroimaging Metadata|MRI/PET acquisition parameters
54	54
55		-To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
	44	+=== **3. Upload Data to Neurodiagnoses** ===
56	56
57		-* **Assign standardized metadata tags** to diagnostic features.
58		-* **Provide contextual explanations** for AI-based classifications.
59		-* **Track temporal disease progression annotations** to identify long-term trends.
	46	+Once preprocessed, data can be uploaded to EBRAINS or GitHub.
60	60
61		-----
	48	+* (((
	49	+**Option 1: Upload to EBRAINS Bucket**
62	62
63		-=== **2. AI-Based Analysis** ===
	51	+* Location: [[EBRAINS Neurodiagnoses Bucket>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
	52	+* Ensure correct metadata tagging before submission.
	53	+)))
	54	+* (((
	55	+**Option 2: Contribute via GitHub Repository**
64	64
65		-==== **Machine Learning & Deep Learning Models** ====
	57	+* Location: [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
	58	+* Create a new folder under /data/ and include dataset description.
	59	+)))
66	66
67		-**Risk Prediction Models:**
	61	+//Note: For large datasets, please contact the project administrators before uploading.//
68	68
69		-* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
	63	+=== **4. Integrate Data into AI Models** ===
70	70
71		-**Biomarker Classification & Probabilistic Imputation:**
	65	+Once uploaded, datasets must be harmonized and formatted before AI model training.
72	72
73		-* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
	67	+==== **Steps for Data Integration** ====
74	74
75		-**Neuroimaging Feature Extraction:**
	69	+* Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
	70	+* Standardize neuroimaging and biomarker formats using harmonization tools.
	71	+* Use machine learning models to handle missing data and feature extraction.
	72	+* Train AI models with newly integrated patient cohorts.
	73	+* Reference: [[Detailed instructions can be found in docs/data_processing.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]].
76	76
77		-* **MRI & EEG data** annotated with **neuroanatomical feature labels**.
78		-
79		-==== **AI-Powered Annotation System** ====
80		-
81		-* Uses **SHAP-based interpretability tools** to explain model decisions.
82		-* Generates **automated clinical annotations** in structured reports.
83		-* Links findings to **standardized medical ontologies** (e.g., **SNOMED, HPO**).
84		-
85	85	----
86	86
87		-=== **3. Diagnostic Framework & Clinical Decision Support** ===
	77	+== **Database Sources Table** ==
88	88
89		-==== **Tridimensional Diagnostic Axes** ====
	79	+=== **Where to Insert This** ===
90	90
91		-**Axis 1: Etiology (Pathogenic Mechanisms)**
	81	+* GitHub: [[docs/data_sources.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_sources.md]]
	82	+* EBRAINS Wiki: Collabs/neurodiagnoses/Data Sources
92	92
93		-* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
94		-* **AI-assisted annotation** provides **causal interpretations** for clinical use.
	84	+=== **Key Databases for Neurodiagnoses** ===
95	95
96		-**Axis 2: Molecular Markers & Biomarkers**
	86	+|=Database|=Focus Area|=Data Type|=Access Link
	87	+|ADNI|Alzheimer's Disease|MRI, PET, CSF, cognitive tests|ADNI
	88	+|PPMI|Parkinson’s Disease|Imaging, biospecimens|[[PPMI>>url:https://www.ppmi-info.org/]]
	89	+|GP2|Genetic Data for PD|Whole-genome sequencing|[[GP2>>url:https://gp2.org/]]
	90	+|Enroll-HD|Huntington’s Disease|Clinical, genetic, imaging|[[Enroll-HD>>url:https://enroll-hd.org/]]
	91	+|GAAIN|Alzheimer's & Cognitive Decline|Multi-source data aggregation|[[GAAIN>>url:https://www.gaain.org/]]
	92	+|UK Biobank|Population-wide studies|Genetic, imaging, health records|[[UK Biobank>>url:https://www.ukbiobank.ac.uk/]]
	93	+|DPUK|Dementia & Aging|Imaging, genetics, lifestyle factors|[[DPUK>>url:https://www.dementiasplatform.uk/]]
	94	+|PRION Registry|Prion Diseases|Clinical and genetic data|[[PRION Registry>>url:https://www.prionalliance.org/]]
	95	+|DECIPHER|Rare Genetic Disorders|Genomic variants|DECIPHER
97	97
98		-* **Integration of CSF, blood, and neuroimaging biomarkers**.
99		-* **Structured annotation** highlights **biological pathways linked to diagnosis**.
	97	+If you know a relevant dataset, submit a proposal in [[GitHub Issues>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]].
100	100
101		-**Axis 3: Neuroanatomoclinical Correlations**
102		-
103		-* **MRI and EEG data** provide anatomical and functional insights.
104		-* **AI-generated progression maps** annotate **brain structure-function relationships**.
105		-
106	106	----
107	107
108		-=== **4. Computational Workflow & Annotation Pipelines** ===
	101	+== **Collaboration & Partnerships** ==
109	109
110		-==== **Data Processing Steps** ====
	103	+=== **Where to Insert This** ===
111	111
112		-**Data Ingestion:**
	105	+* GitHub: [[docs/collaboration.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/collaboration.md]]
	106	+* EBRAINS Wiki: Collabs/neurodiagnoses/Collaborations
113	113
114		-* **Harmonized datasets** stored in **EBRAINS Bucket**.
115		-* **Preprocessing pipelines** clean and standardize data.
	108	+=== **Partnering with Data Providers** ===
116	116
117		-**Feature Engineering:**
	110	+Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
118	118
119		-* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
	112	+* Enable direct API-based data integration for real-time processing.
	113	+* Co-develop harmonized AI-ready datasets with standardized annotations.
	114	+* Secure funding opportunities through joint grant applications.
120	120
121		-**AI-Generated Annotations:**
	116	+=== **Interested in Partnering?** ===
122	122
123		-* **Automated tagging** of diagnostic features in **structured reports**.
124		-* **Explainability modules (SHAP, LIME)** ensure transparency in predictions.
	118	+If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
125	125
126		-**Clinical Decision Support Integration:**
	120	+* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
127	127
128		-* **AI-annotated findings** fed into **interactive dashboards**.
129		-* **Clinicians can adjust, validate, and modify annotations**.
130		-
131	131	----
132	132
133		-=== **5. Validation & Real-World Testing** ===
	124	+== **Final Notes** ==
134	134
135		-==== **Prospective Clinical Study** ====
	126	+Neurodiagnoses continuously expands its data ecosystem to support AI-driven clinical decision-making. Researchers and institutions are encouraged to contribute new datasets and methodologies.
136	136
137		-* **Multi-center validation** of AI-based **annotations & risk stratifications**.
138		-* **Benchmarking against clinician-based diagnoses**.
139		-* **Real-world testing** of AI-powered **structured reporting**.
	128	+For additional technical documentation:
140	140
141		-==== **Quality Assurance & Explainability** ====
	130	+* [[GitHub Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
	131	+* [[EBRAINS Collaboration Page>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
142	142
143		-* **Annotations linked to structured knowledge graphs** for improved transparency.
144		-* **Interactive annotation editor** allows clinicians to validate AI outputs.
145		-
146		-----
147		-
148		-=== **6. Collaborative Development** ===
149		-
150		-The project is **open to contributions** from **researchers, clinicians, and developers**.
151		-
152		-**Key tools include:**
153		-
154		-* **Jupyter Notebooks**: For data analysis and pipeline development.
155		-** Example: **probabilistic imputation**
156		-* **Wiki Pages**: For documenting methods and results.
157		-* **Drive and Bucket**: For sharing code, data, and outputs.
158		-* **Collaboration with related projects**:
159		-** Example: **Beyond the hype: AI in dementia – from early risk detection to disease treatment**
160		-
161		-----
162		-
163		-=== **7. Tools and Technologies** ===
164		-
165		-==== **Programming Languages:** ====
166		-
167		-* **Python** for AI and data processing.
168		-
169		-==== **Frameworks:** ====
170		-
171		-* **TensorFlow** and **PyTorch** for machine learning.
172		-* **Flask** or **FastAPI** for backend services.
173		-
174		-==== **Visualization:** ====
175		-
176		-* **Plotly** and **Matplotlib** for interactive and static visualizations.
177		-
178		-==== **EBRAINS Services:** ====
179		-
180		-* **Collaboratory Lab** for running Notebooks.
181		-* **Buckets** for storing large datasets.
182		-
183		-----
184		-
185		-=== **Why This Matters** ===
186		-
187		-* **The annotation system ensures that AI-generated insights are structured, interpretable, and clinically meaningful.**
188		-* **It enables real-time tracking of disease progression across the three diagnostic axes.**
189		-* **It facilitates integration with electronic health records and decision-support tools, improving AI adoption in clinical workflows.**
	133	+If you experience issues integrating data, open a [[GitHub Issue>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]] or consult the EBRAINS Neurodiagnoses Forum.