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5		-= //A new tridimensional diagnostic framework for complex CNS diseases// =
	5	+= //A new tridimensional diagnostic framework for CNS diseases// =
6	6
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.
	7	+This project is focused on developing a novel nosological and diagnostic framework for 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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10	10	)))
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17	17
18	18	= **Overview** =
19	19
	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.
20	20
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	+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.
22	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	25	The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on:
26	26
27	27	* **Axis 1**: Etiology (genetic or other causes of diseases).
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34	34	* Integration of incomplete datasets using AI-driven probabilistic modeling.
35	35	* Stratification of patients for personalized treatment.
36	36
37		-== **The Role of AI-Powered Annotation** ==
38		-
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	69	== **The case of neurodegenerative diseases** ==
70	70
71	71	There have been described these 3 diagnostic axes:
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78	78	* //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers.
79	79	* //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression.
80	80	* //Tests//: Genetic testing, lifestyle, and cardiovascular screening.
81		-
82		-
83	83	)))
84	84	* (((
85	85	**Axis 2: Molecular Markers**
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87	87	* //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression.
88	88	* //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology.
89	89	* //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET).
90		-
91		-
92	92	)))
93	93	* (((
94	94	**Axis 3: Neuroanatomoclinical**
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105	105	* **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials.
106	106	* **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking.
107	107
	71	+== Who has access? ==
	72	+
	73	+We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
	74	+
108	108	== How to Contribute ==
109	109
110	110	* Access the `/docs` folder for guidelines.
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116	116	* Develop interpretable AI models for diagnosis and progression tracking.
117	117	* Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources.
118	118	* 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!
123	123	)))
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125	125
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127	127
128	128
129		-
130	130	(% class="col-xs-12 col-sm-4" %)
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132	132	{{box title="**Contents**"}}
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140	140	* `/data`: Sample datasets for testing.
141	141	* `/outputs`: Generated models, visualizations, and reports.
142	142	* [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]]
143		-* [[Notebooks>>Notebooks]]
144	144	* [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]]
145	145	* [[to-do-list>>to-do-list]]
146	146	)))