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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	5	----
6	6
7		-=== **1. Data Integration** ===
	7	+== **How to Use External Databases in Neurodiagnoses** ==
8	8
9		-==== **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.
10	10
11		-**Biomedical Ontologies & Databases:**
	11	+=== **Potential Data Sources** ===
12	12
13		-* **Human Phenotype Ontology (HPO)** for symptom annotation.
14		-* **Gene Ontology (GO)** for molecular and cellular processes.
	13	+Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
15	15
16		-**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]]
17	17
18		-* **Evaluate interpretability** using metrics like the **Area Under the Interpretability Curve (AUIC)**.
19		-* **Leverage DEIBO (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
	17	+=== **1. Register for Access** ===
20	20
21		-**Neuroimaging & EEG/MEG Data:**
	19	+Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
22	22
23		-* **MRI volumetric measures** for brain atrophy tracking.
24		-* **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.
25	25
26		-**Clinical & Biomarker Data:**
	24	+=== **2. Download & Prepare Data** ===
27	27
28		-* **CSF biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
29		-* **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.
30	30
31		-**Federated Learning Integration:**
	28	+==== **Supported File Formats** ====
32	32
33		-* **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
34	34
35		-----
	35	+==== **Mandatory Fields for Integration** ====
36	36
37		-==== **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
38	38
39		-To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
	44	+=== **3. Upload Data to Neurodiagnoses** ===
40	40
41		-* **Assign standardized metadata tags** to diagnostic features.
42		-* **Provide contextual explanations** for AI-based classifications.
43		-* **Track temporal disease progression annotations** to identify long-term trends.
	46	+Once preprocessed, data can be uploaded to EBRAINS or GitHub.
44	44
45		-----
	48	+* (((
	49	+**Option 1: Upload to EBRAINS Bucket**
46	46
47		-=== **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**
48	48
49		-==== **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	+)))
50	50
51		-**Risk Prediction Models:**
	61	+//Note: For large datasets, please contact the project administrators before uploading.//
52	52
53		-* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
	63	+=== **4. Integrate Data into AI Models** ===
54	54
55		-**Biomarker Classification & Probabilistic Imputation:**
	65	+Once uploaded, datasets must be harmonized and formatted before AI model training.
56	56
57		-* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
	67	+==== **Steps for Data Integration** ====
58	58
59		-**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]].
60	60
61		-* **MRI & EEG data** annotated with **neuroanatomical feature labels**.
62		-
63		-==== **AI-Powered Annotation System** ====
64		-
65		-* Uses **SHAP-based interpretability tools** to explain model decisions.
66		-* Generates **automated clinical annotations** in structured reports.
67		-* Links findings to **standardized medical ontologies** (e.g., **SNOMED, HPO**).
68		-
69	69	----
70	70
71		-=== **3. Diagnostic Framework & Clinical Decision Support** ===
	77	+== **Database Sources Table** ==
72	72
73		-==== **Tridimensional Diagnostic Axes** ====
	79	+=== **Where to Insert This** ===
74	74
75		-**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
76	76
77		-* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
78		-* **AI-assisted annotation** provides **causal interpretations** for clinical use.
	84	+=== **Key Databases for Neurodiagnoses** ===
79	79
80		-**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
81	81
82		-* **Integration of CSF, blood, and neuroimaging biomarkers**.
83		-* **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]].
84	84
85		-**Axis 3: Neuroanatomoclinical Correlations**
86		-
87		-* **MRI and EEG data** provide anatomical and functional insights.
88		-* **AI-generated progression maps** annotate **brain structure-function relationships**.
89		-
90	90	----
91	91
92		-=== **4. Computational Workflow & Annotation Pipelines** ===
	101	+== **Collaboration & Partnerships** ==
93	93
94		-==== **Data Processing Steps** ====
	103	+=== **Where to Insert This** ===
95	95
96		-**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
97	97
98		-* **Harmonized datasets** stored in **EBRAINS Bucket**.
99		-* **Preprocessing pipelines** clean and standardize data.
	108	+=== **Partnering with Data Providers** ===
100	100
101		-**Feature Engineering:**
	110	+Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
102	102
103		-* **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.
104	104
105		-**AI-Generated Annotations:**
	116	+=== **Interested in Partnering?** ===
106	106
107		-* **Automated tagging** of diagnostic features in **structured reports**.
108		-* **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.
109	109
110		-**Clinical Decision Support Integration:**
	120	+* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
111	111
112		-* **AI-annotated findings** fed into **interactive dashboards**.
113		-* **Clinicians can adjust, validate, and modify annotations**.
114		-
115	115	----
116	116
117		-=== **5. Validation & Real-World Testing** ===
	124	+== **Final Notes** ==
118	118
119		-==== **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.
120	120
121		-* **Multi-center validation** of AI-based **annotations & risk stratifications**.
122		-* **Benchmarking against clinician-based diagnoses**.
123		-* **Real-world testing** of AI-powered **structured reporting**.
	128	+For additional technical documentation:
124	124
125		-==== **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/]]
126	126
127		-* **Annotations linked to structured knowledge graphs** for improved transparency.
128		-* **Interactive annotation editor** allows clinicians to validate AI outputs.
129		-
130		-----
131		-
132		-=== **6. Collaborative Development** ===
133		-
134		-The project is **open to contributions** from **researchers, clinicians, and developers**.
135		-
136		-**Key tools include:**
137		-
138		-* **Jupyter Notebooks**: For data analysis and pipeline development.
139		-** Example: **probabilistic imputation**
140		-* **Wiki Pages**: For documenting methods and results.
141		-* **Drive and Bucket**: For sharing code, data, and outputs.
142		-* **Collaboration with related projects**:
143		-** Example: **Beyond the hype: AI in dementia – from early risk detection to disease treatment**
144		-
145		-----
146		-
147		-=== **7. Tools and Technologies** ===
148		-
149		-==== **Programming Languages:** ====
150		-
151		-* **Python** for AI and data processing.
152		-
153		-==== **Frameworks:** ====
154		-
155		-* **TensorFlow** and **PyTorch** for machine learning.
156		-* **Flask** or **FastAPI** for backend services.
157		-
158		-==== **Visualization:** ====
159		-
160		-* **Plotly** and **Matplotlib** for interactive and static visualizations.
161		-
162		-==== **EBRAINS Services:** ====
163		-
164		-* **Collaboratory Lab** for running Notebooks.
165		-* **Buckets** for storing large datasets.
166		-
167		-----
168		-
169		-=== **Why This Matters** ===
170		-
171		-* **The annotation system ensures that AI-generated insights are structured, interpretable, and clinically meaningful.**
172		-* **It enables real-time tracking of disease progression across the three diagnostic axes.**
173		-* **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.