Changes for page Neurodiagnoses
Last modified by manuelmenendez on 2025/03/03 22:46
From version 33.1
edited by manuelmenendez
on 2025/02/01 13:54
on 2025/02/01 13:54
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To version 5.1
edited by manuelmenendez
on 2025/01/27 23:04
on 2025/01/27 23:04
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... ... @@ -2,10 +2,9 @@ 2 2 ((( 3 3 (% class="container" %) 4 4 ((( 5 -= //A new tridimensionaldiagnostic framework for CNS diseases//=5 += Neurodiagnoses = 6 6 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. 7 +This project is focused on developing a novel nosological and diagnostic framework for neurological diseases. Using advanced AI techniques and integrating data from neuroimaging, biomarkers, and biomedical ontologies, we aim to create a structured, interpretable, and scalable diagnostic tool. 9 9 ))) 10 10 ))) 11 11 ... ... @@ -13,101 +13,26 @@ 13 13 ((( 14 14 (% class="col-xs-12 col-sm-8" %) 15 15 ((( 16 -= What is this about and whatcan I find here? =15 += What can I find here? = 17 17 18 -= **Overview**=17 +== Who has access? == 19 19 20 - T19 +We welcome contributions from the global community. Let’s build the future of neurological diagnostics together! 21 21 22 - Theclassificationand diagnosis of **central nervoussystem (CNS) diseases** have long been constrainedby **traditional phenotype-based approaches**, which often fail to capturethe**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.21 +== How to Contribute: == 23 23 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**. 25 - 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**. 27 - 28 -=== **Project Aim** === 29 - 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**. 31 - 32 -The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on: 33 - 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). 37 - 38 -This methodology enables: 39 - 40 -* Greater precision in diagnosis. 41 -* Integration of incomplete datasets using AI-driven probabilistic modeling. 42 -* Stratification of patients for personalized treatment. 43 - 44 -== **The Role of AI-Powered Annotation** == 45 - 46 -To enhance **standardization, interpretability, and clinical application**, the framework integrates **an AI-powered annotation system**, which: 47 - 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). 53 - 54 -== **The case of neurodegenerative diseases** == 55 - 56 -There have been described these 3 diagnostic axes: 57 - 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"]] 59 - 60 -* ((( 61 -**Axis 1: Etiology** 62 - 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. 66 -))) 67 -* ((( 68 -**Axis 2: Molecular Markers** 69 - 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). 73 -))) 74 -* ((( 75 -**Axis 3: Neuroanatomoclinical** 76 - 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. 80 -))) 81 - 82 -== **Applications** == 83 - 84 -This system enhances: 85 - 86 -* **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials. 87 -* **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking. 88 - 89 -== How to Contribute == 90 - 91 91 * Access the `/docs` folder for guidelines. 92 92 * Use `/code` for the latest AI pipelines. 93 93 * Share feedback and ideas in the wiki discussion pages. 94 94 95 -== Key Objectives == 27 +== Key Objectives: == 96 96 97 97 * Develop interpretable AI models for diagnosis and progression tracking. 98 98 * Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources. 99 99 * Foster collaboration among neuroscientists, AI researchers, and clinicians. 100 - 101 -== Who has access? == 102 - 103 -We welcome contributions from the global community. Let’s build the future of neurological diagnostics together! 104 104 ))) 105 105 106 106 107 - 108 - 109 - 110 - 111 111 (% class="col-xs-12 col-sm-4" %) 112 112 ((( 113 113 {{box title="**Contents**"}} ... ... @@ -114,14 +114,11 @@ 114 114 {{toc/}} 115 115 {{/box}} 116 116 117 -== Main contents == 41 +== Main contents: == 118 118 119 119 * `/docs`: Documentation and contribution guidelines. 120 120 * `/code`: Machine learning pipelines and scripts. 121 121 * `/data`: Sample datasets for testing. 122 122 * `/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]] 126 126 ))) 127 127 )))
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