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1		-== **Overview** ==
	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	5	----
6	6
7		-== **How to Use External Databases in Neurodiagnoses** ==
	7	+=== **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.
	9	+==== **Data Sources** ====
10	10
11		-=== **Potential Data Sources** ===
	11	+**Biomedical Ontologies & Databases:**
12	12
13		-Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
	13	+* **Human Phenotype Ontology (HPO)** for symptom annotation.
	14	+* **Gene Ontology (GO)** for molecular and cellular processes.
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	+**Dimensionality Reduction and Interpretability:**
16	16
17		-=== **1. Register for Access** ===
	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.
18	18
19		-Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
	21	+**Neuroimaging & EEG/MEG Data:**
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.
	23	+* **MRI volumetric measures** for brain atrophy tracking.
	24	+* **EEG functional connectivity patterns** (AI-Mind).
23	23
24		-=== **2. Download & Prepare Data** ===
	26	+**Clinical & Biomarker Data:**
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.
	28	+* **CSF biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
	29	+* **Sleep monitoring and actigraphy data** (ADIS).
27	27
28		-==== **Supported File Formats** ====
	31	+**Federated Learning Integration:**
29	29
30		-* Tabular Data: .csv, .tsv
31		-* Neuroimaging Data: .nii, .dcm
32		-* Genomic Data: .fasta, .vcf
33		-* Clinical Metadata: .json, .xml
	33	+* **Secure multi-center data harmonization** (PROMINENT).
34	34
35		-==== **Mandatory Fields for Integration** ====
	35	+----
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
	37	+==== **Annotation System for Multi-Modal Data** ====
43	43
44		-=== **3. Upload Data to Neurodiagnoses** ===
	39	+To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
45	45
46		-Once preprocessed, data can be uploaded to EBRAINS or GitHub.
	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.
47	47
48		-* (((
49		-**Option 1: Upload to EBRAINS Bucket**
	45	+----
50	50
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**
	47	+=== **2. AI-Based Analysis** ===
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.
59		-)))
	49	+==== **Machine Learning & Deep Learning Models** ====
60	60
61		-//Note: For large datasets, please contact the project administrators before uploading.//
	51	+**Risk Prediction Models:**
62	62
63		-=== **4. Integrate Data into AI Models** ===
	53	+* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
64	64
65		-Once uploaded, datasets must be harmonized and formatted before AI model training.
	55	+**Biomarker Classification & Probabilistic Imputation:**
66	66
67		-==== **Steps for Data Integration** ====
	57	+* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
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]].
	59	+**Neuroimaging Feature Extraction:**
74	74
	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	+
75	75	----
76	76
77		-== **Database Sources Table** ==
	71	+=== **3. Diagnostic Framework & Clinical Decision Support** ===
78	78
79		-=== **Where to Insert This** ===
	73	+==== **Tridimensional Diagnostic Axes** ====
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
	75	+**Axis 1: Etiology (Pathogenic Mechanisms)**
83	83
84		-=== **Key Databases for Neurodiagnoses** ===
	77	+* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
	78	+* **AI-assisted annotation** provides **causal interpretations** for clinical use.
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
	80	+**Axis 2: Molecular Markers & Biomarkers**
96	96
97		-If you know a relevant dataset, submit a proposal in [[GitHub Issues>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]].
	82	+* **Integration of CSF, blood, and neuroimaging biomarkers**.
	83	+* **Structured annotation** highlights **biological pathways linked to diagnosis**.
98	98
	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	+
99	99	----
100	100
101		-== **Collaboration & Partnerships** ==
	92	+=== **4. Computational Workflow & Annotation Pipelines** ===
102	102
103		-=== **Where to Insert This** ===
	94	+==== **Data Processing Steps** ====
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
	96	+**Data Ingestion:**
107	107
108		-=== **Partnering with Data Providers** ===
	98	+* **Harmonized datasets** stored in **EBRAINS Bucket**.
	99	+* **Preprocessing pipelines** clean and standardize data.
109	109
110		-Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
	101	+**Feature Engineering:**
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.
	103	+* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
115	115
116		-=== **Interested in Partnering?** ===
	105	+**AI-Generated Annotations:**
117	117
118		-If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
	107	+* **Automated tagging** of diagnostic features in **structured reports**.
	108	+* **Explainability modules (SHAP, LIME)** ensure transparency in predictions.
119	119
120		-* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
	110	+**Clinical Decision Support Integration:**
121	121
	112	+* **AI-annotated findings** fed into **interactive dashboards**.
	113	+* **Clinicians can adjust, validate, and modify annotations**.
	114	+
122	122	----
123	123
124		-== **Final Notes** ==
	117	+=== **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.
	119	+==== **Prospective Clinical Study** ====
127	127
128		-For additional technical documentation:
	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**.
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/]]
	125	+==== **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.
	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.**