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5	5	=== **Workflow** ===
6	6
7	7	1. (((
8		-**We Use GitHub to [[Store and develop AI models, scripts, and annotation pipelines.>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]**
	8	+**We Use GitHub for AI Development**
9	9
10	10	* Create a **GitHub repository** for AI scripts and models.
11	11	* Use **GitHub Projects** to manage research milestones.
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22	22
23	23	=== **1. Data Integration** ===
24	24
25		-=== **EBRAINS Medical Informatics Platform (MIP)**. ===
26		-
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.
28		-
29		-==== How It Works ====
30		-
31		-
32		-1. (((
33		-**Authentication & API Access:**
34		-
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:**
40		-
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:**
46		-
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		-)))
51		-
52		-==== Implementation Steps ====
53		-
54		-
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**.
59		-
60		-For more detailed instructions, please refer to the **[[MIP Documentation>>url:https://mip.ebrains.eu/]]**.
61		-
62		-----
63		-
64		-=== Data Processing & Integration with Clinica.Run ===
65		-
66		-Neurodiagnoses now supports **Clinica.Run**, an open-source neuroimaging platform designed for **multimodal data processing and reproducible neuroscience workflows**.
67		-
68		-==== How It Works ====
69		-
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**.
76		-)))
77		-1. (((
78		-**Automated Biomarker Extraction:**
79		-
80		-* Standardized extraction of **volumetric, metabolic, and functional biomarkers**.
81		-* Integration with machine learning models in Neurodiagnoses.
82		-)))
83		-1. (((
84		-**Data Security & Compliance:**
85		-
86		-* Clinica.Run operates in **compliance with GDPR and HIPAA**.
87		-* Neuroimaging data remains **within the original storage environment**.
88		-)))
89		-
90		-==== Implementation Steps ====
91		-
92		-
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.
97		-
98		-For further information, refer to **[[Clinica.Run Documentation>>url:https://clinica.run/]]**.
99		-
100		-==== ====
101		-
102	102	==== **Data Sources** ====
103	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	106	**Biomedical Ontologies & Databases:**
107	107
108	108	* **Human Phenotype Ontology (HPO)** for symptom annotation.
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111	111	**Dimensionality Reduction and Interpretability:**
112	112
113	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.
	35	+* **Leverage DEIBO (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
115	115
116	116	**Neuroimaging & EEG/MEG Data:**
117	117
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263	263
264	264	=== **Why This Matters** ===
265	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.
	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.**