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3	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**.
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5		-=== **Workflow** ===
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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]]**
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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**
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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	----
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23	23	=== **1. Data Integration** ===
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32	32	**Dimensionality Reduction and Interpretability:**
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34	34	* **Evaluate interpretability** using metrics like the **Area Under the Interpretability Curve (AUIC)**.
35		-* **Leverage [[DEIBO>>https://github.com/Mellandd/DEIBO]] (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
	19	+* **Leverage DEIBO (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
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37	37	**Neuroimaging & EEG/MEG Data:**
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