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5		-= //A new tridimensional diagnostic framework for CNS conditions// =
	5	+= //A new tridimensional diagnostic framework for complex CNS diseases// =
6	6
7		-This project is focused on developing a novel nosological and diagnostic framework for neurological diseases by using advanced AI techniques and integrating data from neuroimaging, biomarkers, and biomedical ontologies.
	7	+This project is focused on developing a novel nosological and diagnostic framework for complex CNS diseases by using advanced AI techniques and integrating data from neuroimaging, biomarkers, and biomedical ontologies.
8	8	We aim to create a structured, interpretable, and scalable diagnostic tool.
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16	16	= What is this about and what can I find here? =
17	17
18		-== **Overview** ==
	18	+= **Overview** =
19	19
20		-The //Tridimensional Diagnostic Framework// redefines how neurodegenerative diseases (NDDs) are classified by focusing on:
21	21
22		-* **Axis 1**: Etiology (genetic/sporadic and environmental factors).
23		-* **Axis 2**: Molecular Markers (biomarkers and proteinopathies).
	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.
	22	+
	23	+Neurodiagnoses is an open-source AI-powered diagnostic system designed for complex CNS disorders, including neurodegenerative diseases, autoimmune encephalopathies, prion disorders, and genetic syndromes. 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.
	24	+
	25	+The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on:
	26	+
	27	+* **Axis 1**: Etiology (genetic or other causes of diseases).
	28	+* **Axis 2**: Molecular Markers (biomarkers).
24	24	* **Axis 3**: Neuroanatomoclinical correlations (linking clinical symptoms to structural changes in the nervous system).
25	25
26	26	This methodology enables:
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29	29	* Integration of incomplete datasets using AI-driven probabilistic modeling.
30	30	* Stratification of patients for personalized treatment.
31	31
32		-== **Diagnostic Axes** ==
	37	+== **The Role of AI-Powered Annotation** ==
33	33
	39	+To enhance standardization, interpretability, and clinical application, the framework integrates an AI-powered annotation system, which:
	40	+
	41	+* Assigns structured metadata tags to diagnostic features.
	42	+* Provides real-time contextual explanations for AI-based classifications.
	43	+* Tracks longitudinal disease progression using timestamped AI annotations.
	44	+* Improves AI model transparency through interpretability tools (e.g., SHAP analysis).
	45	+* Facilitates decision-making for clinicians by linking annotations to standardized biomedical ontologies (SNOMED, HPO).
	46	+
	47	+Neurodiagnoses provides two complementary AI-driven diagnostic approaches:
	48	+
	49	+1. Traditional Probabilistic Diagnosis
	50	+
	51	+* AI provides multiple possible diagnoses, each assigned a probability percentage based on biomarker, imaging, and clinical data.
	52	+* Example Output:
	53	+** 75% Alzheimer's Disease
	54	+** 20% Lewy Body Dementia
	55	+** 5% Vascular Dementia
	56	+* Useful for differential diagnosis and treatment decision-making.
	57	+
	58	+2. Tridimensional Diagnosis
	59	+
	60	+* Diagnoses are structured based on:
	61	+(1) Etiology (genetic, autoimmune, metabolic, infectious)
	62	+(2) Molecular Biomarkers (amyloid-beta, tau, inflammatory markers, EEG patterns)
	63	+(3) Neuroanatomoclinical Correlations (brain atrophy, connectivity alterations)
	64	+* This approach enables precise disease subtyping and biologically meaningful classification, particularly useful to track progression over time.
	65	+
	66	+For every patient case, both systems will be offered, allowing clinicians to compare AI-generated probabilistic diagnosis with a structured tridimensional classification.
	67	+
	68	+
	69	+== **The case of neurodegenerative diseases** ==
	70	+
	71	+There have been described these 3 diagnostic axes:
	72	+
	73	+[[Neurodegenerative diseases can be studied and classified in a tridimensional scheme with three axes: anatomic–clinical, molecular, and etiologic. CSF, cerebrospinal fluid; FDG, fluorodeoxyglucose; MRI, magnetic resonance imaging; PET, positron emission tomography.>>image:tridimensional.png||alt="tridimensional view of neurodegenerative diseases"]]
	74	+
34	34	* (((
35	35	**Axis 1: Etiology**
36	36
37	37	* //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers.
38	38	* //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression.
39		-* //Tests//: Genetic testing, lifestyle and cardiovascular screening.
	80	+* //Tests//: Genetic testing, lifestyle, and cardiovascular screening.
	81	+
	82	+
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41	41	* (((
42	42	**Axis 2: Molecular Markers**
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44	44	* //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression.
45	45	* //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology.
46	46	* //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET).
	90	+
	91	+
47	47	)))
48	48	* (((
49	49	**Axis 3: Neuroanatomoclinical**
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60	60	* **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials.
61	61	* **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking.
62	62
63		-== Who has access? ==
64		-
65		-We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
66		-
67	67	== How to Contribute ==
68	68
69	69	* Access the `/docs` folder for guidelines.
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75	75	* Develop interpretable AI models for diagnosis and progression tracking.
76	76	* Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources.
77	77	* Foster collaboration among neuroscientists, AI researchers, and clinicians.
	119	+
	120	+== Who has access? ==
	121	+
	122	+We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
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	126	+
	127	+
	128	+
	129	+
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83	83	{{box title="**Contents**"}}
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90	90	* `/code`: Machine learning pipelines and scripts.
91	91	* `/data`: Sample datasets for testing.
92	92	* `/outputs`: Generated models, visualizations, and reports.
	142	+* [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]]
	143	+* [[Notebooks>>Notebooks]]
	144	+* [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]]
	145	+* [[to-do-list>>to-do-list]]
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tridimensional.png

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	1	+XWiki.manuelmenendez

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