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