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18	18	= **Overview** =
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	20	+The classification and diagnosis of central nervous system (CNS) diseases have long been constrained by traditional phenotypic approaches that fail to capture the underlying pathophysiological mechanisms, molecular biomarkers, and neuroanatomical changes that drive disease progression. For instance, neurodegenerative and psychiatric disorders exhibit significant clinical overlap, co-pathology, and heterogeneity, a new diagnostic framework is urgently needed—one that shifts from symptom-based classifications toward an etiology-driven, tridimensional system integrating genetics, proteomics, neuroimaging, and computational modeling. By leveraging AI, multi-modal biomarkers, and precision medicine, this framework aims to provide a more objective, scalable, and biologically grounded approach to diagnosing and managing CNS diseases, ultimately leading to earlier detection, personalized interventions, and improved patient outcomes.
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21		-The classification and diagnosis of **central nervous system (CNS) diseases** have long been constrained by **traditional phenotype-based approaches**, which often fail to capture the **complex pathophysiological mechanisms, molecular biomarkers, and neuroanatomical changes** that drive disease progression. **Neurodegenerative and psychiatric disorders**, for example, exhibit significant **clinical overlap, co-pathology, and heterogeneity**, making current diagnostic models insufficient.
	22	+The project aims to develop a tridimensional diagnostic framework with an AI-powered annotation system, integrating etiology, molecular biomarkers, and neuroanatomoclinical correlations for precise and scalable CNS disease diagnostics.
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23		-This project proposes a **new diagnostic framework**—one that **shifts from symptom-based classifications** to an **etiology-driven, tridimensional system**. By integrating **genetics, proteomics, neuroimaging, computational modeling, and AI-powered annotations**, this approach aims to provide a **more precise, scalable, and biologically grounded method for diagnosing and managing CNS diseases**.
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25		-The **AI-powered annotation system** plays a critical role by **structuring, interpreting, and tracking multi-modal data**, ensuring **real-time disease progression analysis, clinician decision support, and personalized treatment pathways**.
26		-
27		-=== **Project Aim** ===
28		-
29		-The project aims to develop a **tridimensional diagnostic framework** with an **AI-powered annotation system**, integrating **etiology, molecular biomarkers, and neuroanatomoclinical correlations** for **precise, standardized, and scalable CNS disease diagnostics**.
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31	31	The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on:
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33	33	* **Axis 1**: Etiology (genetic or other causes of diseases).
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40	40	* Integration of incomplete datasets using AI-driven probabilistic modeling.
41	41	* Stratification of patients for personalized treatment.
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43		-== **The Role of AI-Powered Annotation** ==
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45		-To enhance **standardization, interpretability, and clinical application**, the framework integrates **an AI-powered annotation system**, which:
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47		-* **Assigns structured metadata tags** to diagnostic features.
48		-* **Provides real-time contextual explanations** for AI-based classifications.
49		-* **Tracks longitudinal disease progression** using timestamped AI annotations.
50		-* **Improves AI model transparency** through interpretability tools (e.g., SHAP analysis).
51		-* **Facilitates decision-making for clinicians** by linking annotations to standardized biomedical ontologies (SNOMED, HPO).
52		-
53	53	== **The case of neurodegenerative diseases** ==
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55	55	There have been described these 3 diagnostic axes:
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85	85	* **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials.
86	86	* **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking.
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	71	+== Who has access? ==
	72	+
	73	+We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
	74	+
88	88	== How to Contribute ==
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90	90	* Access the `/docs` folder for guidelines.
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96	96	* Develop interpretable AI models for diagnosis and progression tracking.
97	97	* Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources.
98	98	* Foster collaboration among neuroscientists, AI researchers, and clinicians.
99		-
100		-== Who has access? ==
101		-
102		-We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
103	103	)))
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109		-
110	110	(% class="col-xs-12 col-sm-4" %)
111	111	(((
112	112	{{box title="**Contents**"}}
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120	120	* `/data`: Sample datasets for testing.
121	121	* `/outputs`: Generated models, visualizations, and reports.
122	122	* [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]]
123		-* [[Notebooks>>Notebooks]]
124	124	* [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]]
125	125	* [[to-do-list>>to-do-list]]
126	126	)))