Wiki source code of Neurodiagnoses

Version 33.1 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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22 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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24 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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26 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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28 === **Project Aim** ===
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30 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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32 The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on:
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34 * **Axis 1**: Etiology (genetic or other causes of diseases).
35 * **Axis 2**: Molecular Markers (biomarkers).
36 * **Axis 3**: Neuroanatomoclinical correlations (linking clinical symptoms to structural changes in the nervous system).
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38 This methodology enables:
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40 * Greater precision in diagnosis.
41 * Integration of incomplete datasets using AI-driven probabilistic modeling.
42 * Stratification of patients for personalized treatment.
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44 == **The Role of AI-Powered Annotation** ==
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46 To enhance **standardization, interpretability, and clinical application**, the framework integrates **an AI-powered annotation system**, which:
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48 * **Assigns structured metadata tags** to diagnostic features.
49 * **Provides real-time contextual explanations** for AI-based classifications.
50 * **Tracks longitudinal disease progression** using timestamped AI annotations.
51 * **Improves AI model transparency** through interpretability tools (e.g., SHAP analysis).
52 * **Facilitates decision-making for clinicians** by linking annotations to standardized biomedical ontologies (SNOMED, HPO).
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54 == **The case of neurodegenerative diseases** ==
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56 There have been described these 3 diagnostic axes:
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58 [[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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61 **Axis 1: Etiology**
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63 * //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers.
64 * //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression.
65 * //Tests//: Genetic testing, lifestyle, and cardiovascular screening.
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68 **Axis 2: Molecular Markers**
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70 * //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression.
71 * //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology.
72 * //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET).
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75 **Axis 3: Neuroanatomoclinical**
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77 * //Description//: Links clinical symptoms to neuroanatomical changes, such as atrophy or functional impairments.
78 * //Examples//: Hippocampal atrophy correlating with memory deficits.
79 * //Tests//: MRI volumetrics, FDG-PET, neuropsychological evaluations.
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82 == **Applications** ==
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84 This system enhances:
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86 * **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials.
87 * **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking.
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89 == How to Contribute ==
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91 * Access the `/docs` folder for guidelines.
92 * Use `/code` for the latest AI pipelines.
93 * Share feedback and ideas in the wiki discussion pages.
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95 == Key Objectives ==
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97 * Develop interpretable AI models for diagnosis and progression tracking.
98 * Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources.
99 * Foster collaboration among neuroscientists, AI researchers, and clinicians.
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101 == Who has access? ==
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103 We welcome contributions from the global community. Let’s build the future of neurological diagnostics together!
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113 {{box title="**Contents**"}}
114 {{toc/}}
115 {{/box}}
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117 == Main contents ==
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119 * `/docs`: Documentation and contribution guidelines.
120 * `/code`: Machine learning pipelines and scripts.
121 * `/data`: Sample datasets for testing.
122 * `/outputs`: Generated models, visualizations, and reports.
123 * [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]]
124 * [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]]
125 * [[to-do-list>>to-do-list]]
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