Changes for page Neurodiagnoses

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26 26  
27 27  === **Project Aim** ===
28 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.
29 +Neurodiagnoses is an open-source AI-powered diagnostic system designed for complex central nervous system (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.
30 30  
31 31  The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on:
32 32  
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50 50  * Improves AI model transparency through interpretability tools (e.g., SHAP analysis).
51 51  * Facilitates decision-making for clinicians by linking annotations to standardized biomedical ontologies (SNOMED, HPO).
52 52  
53 +Neurodiagnoses provides two complementary AI-driven diagnostic approaches:
54 +
55 +1. Traditional Probabilistic Diagnosis
56 +
57 +* AI provides multiple possible diagnoses, each assigned a probability percentage based on biomarker, imaging, and clinical data.
58 +* Example Output:
59 +
60 +>
61 +
62 +{{{75% Alzheimer's Disease
63 +20% Lewy Body Dementia
64 +5% Vascular Dementia
65 +}}}
66 +
67 +* Useful for differential diagnosis and treatment decision-making.
68 +
69 +2. Tridimensional Diagnosis
70 +
71 +* Diagnoses are structured based on:
72 +(1) Etiology (genetic, autoimmune, metabolic, infectious)
73 +(2) Molecular Biomarkers (amyloid-beta, tau, inflammatory markers, EEG patterns)
74 +(3) Neuroanatomoclinical Correlations (brain atrophy, connectivity alterations)
75 +* This approach enables precise disease subtyping and biologically meaningful classification.
76 +
77 +For every patient case, both systems will be offered, allowing clinicians to compare AI-generated probabilistic diagnosis with a structured tridimensional classification.
78 +
79 +
53 53  == **The case of neurodegenerative diseases** ==
54 54  
55 55  There have been described these 3 diagnostic axes: