Wiki source code of Neurodiagnoses

Version 34.1 by manuelmenendez on 2025/02/01 13:54
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5 = //A new tridimensional diagnostic framework for CNS diseases// =
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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 We aim to create a structured, interpretable, and scalable diagnostic tool.
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16 = What is this about and what can I find here? =
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18 = **Overview** =
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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.
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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**.
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27 === **Project Aim** ===
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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 The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on:
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33 * **Axis 1**: Etiology (genetic or other causes of diseases).
34 * **Axis 2**: Molecular Markers (biomarkers).
35 * **Axis 3**: Neuroanatomoclinical correlations (linking clinical symptoms to structural changes in the nervous system).
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37 This methodology enables:
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39 * Greater precision in diagnosis.
40 * Integration of incomplete datasets using AI-driven probabilistic modeling.
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).
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53 == **The case of neurodegenerative diseases** ==
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55 There have been described these 3 diagnostic axes:
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57 [[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"]]
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60 **Axis 1: Etiology**
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62 * //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers.
63 * //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression.
64 * //Tests//: Genetic testing, lifestyle, and cardiovascular screening.
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67 **Axis 2: Molecular Markers**
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69 * //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression.
70 * //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology.
71 * //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET).
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74 **Axis 3: Neuroanatomoclinical**
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76 * //Description//: Links clinical symptoms to neuroanatomical changes, such as atrophy or functional impairments.
77 * //Examples//: Hippocampal atrophy correlating with memory deficits.
78 * //Tests//: MRI volumetrics, FDG-PET, neuropsychological evaluations.
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81 == **Applications** ==
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83 This system enhances:
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85 * **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials.
86 * **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking.
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88 == How to Contribute ==
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90 * Access the `/docs` folder for guidelines.
91 * Use `/code` for the latest AI pipelines.
92 * Share feedback and ideas in the wiki discussion pages.
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94 == Key Objectives ==
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96 * Develop interpretable AI models for diagnosis and progression tracking.
97 * Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources.
98 * Foster collaboration among neuroscientists, AI researchers, and clinicians.
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100 == Who has access? ==
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102 We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
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112 {{box title="**Contents**"}}
113 {{toc/}}
114 {{/box}}
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116 == Main contents ==
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118 * `/docs`: Documentation and contribution guidelines.
119 * `/code`: Machine learning pipelines and scripts.
120 * `/data`: Sample datasets for testing.
121 * `/outputs`: Generated models, visualizations, and reports.
122 * [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]]
123 * [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]]
124 * [[to-do-list>>to-do-list]]
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