Changes for page Neurodiagnoses
Last modified by manuelmenendez on 2025/03/03 22:46
From version 45.1
edited by manuelmenendez
on 2025/02/08 17:20
on 2025/02/08 17:20
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To version 21.1
edited by manuelmenendez
on 2025/01/28 00:30
on 2025/01/28 00:30
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... ... @@ -2,9 +2,9 @@ 2 2 ((( 3 3 (% class="container" %) 4 4 ((( 5 -= //A new tridimensional diagnostic framework for complexCNSdiseases// =5 += //A new tridimensional diagnostic framework for neurodegenerative diseases// = 6 6 7 -This project is focused on developing a novel nosological and diagnostic framework for complexCNSdiseases 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 neurodegenerative 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. 9 9 ))) 10 10 ))) ... ... @@ -15,62 +15,31 @@ 15 15 ((( 16 16 = What is this about and what can I find here? = 17 17 18 -= **Overview** = 18 +== **Overview** == 19 19 20 +The //Tridimensional Diagnostic Framework// redefines how neurodegenerative diseases (NDD) are classified by focusing on: 20 20 21 -The classification and diagnosis of central nervous system (CNS) diseases have long been constrained by traditional, phenotype-based approaches that often fail to capture the complex interplay of pathophysiological mechanisms, molecular biomarkers, and neuroanatomical changes. Neurodiagnoses redefines this landscape by integrating advanced AI with multi-modal data—including genetics, neuroimaging, biomarkers, and digital health records—to create a more precise, scalable, and data-driven diagnostic system. 22 +* **Axis 1**: Etiology (genetic or other causes of diseases). 23 +* **Axis 2**: Molecular Markers (biomarkers). 24 +* **Axis 3**: Neuroanatomoclinical correlations (linking clinical symptoms to structural changes in the nervous system). 22 22 23 - Indditionto these clinical diagnosticapproaches,Neurodiagnoseshasxpandedintoa research-orientedplatformthroughtheintegration of **CNS DigitalTwins**. Thiscutting-edgeconcept involvescreatingapersonalizeddigital replicaof a patient’sCNSby incorporatingmulti-omicsdata(proteomics,genomics,lipidomics,transcriptomics),variousuroimagingmodalities, anddigitalhealth information. These digital twins enable simulations ofdisease progression, supporthediscoveryof novel biomarkers, andhelp identify new therapeutictargets.26 +[[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"]] 24 24 25 -On this page, you will find: 26 26 27 -* Detailed descriptions of both the clinical diagnostic tools and the research framework. 28 -* Access to our AI models, data processing pipelines, and digital twin simulations. 29 -* Collaborative resources for researchers, clinicians, and AI developers. 30 -* Guidelines and instructions on how to contribute to and expand the project. 29 +This methodology enables: 31 31 32 -== **The role of AI-powered annotation** == 31 +* Greater precision in diagnosis. 32 +* Integration of incomplete datasets using AI-driven probabilistic modeling. 33 +* Stratification of patients for personalized treatment. 33 33 34 - Toenhancestandardization, interpretability, andclinicalapplication, the framework integrates anAI-powered annotationsystem,which:35 +== **Diagnostic Axes** == 35 35 36 -* Assign structured metadata tags to diagnostic features. 37 -* Provides real-time contextual explanations for AI-based classifications. 38 -* Tracks longitudinal disease progression using timestamped AI annotations. 39 -* Improves AI model transparency through interpretability tools (e.g., SHAP analysis). 40 -* Facilitates decision-making for clinicians by linking annotations to standardized biomedical ontologies (SNOMED, HPO). 41 - 42 -Neurodiagnoses provides two complementary AI-driven diagnostic approaches: 43 - 44 -1. Traditional Probabilistic Diagnosis 45 - 46 -* AI provides multiple possible diagnoses, each assigned a probability percentage based on biomarker, imaging, and clinical data. 47 -* Useful for differential diagnosis and treatment decision-making. 48 - 49 -2. Tridimensional Diagnosis 50 - 51 -* Diagnoses are structured based on: 52 -(1) Etiology (genetic, autoimmune, metabolic, infectious) 53 -(2) Molecular Biomarkers (amyloid-beta, tau, inflammatory markers, EEG patterns) 54 -(3) Neuroanatomoclinical Correlations (brain atrophy, connectivity alterations) 55 -* This approach enables precise disease subtyping and biologically meaningful classification, particularly useful for tracking progression over time. 56 - 57 -Both systems will be offered for every patient case, allowing clinicians to compare AI-generated probabilistic diagnosis with a structured tridimensional classification. 58 - 59 - 60 -== **The case of neurodegenerative diseases** == 61 - 62 -There have been described these 3 diagnostic axes: 63 - 64 -[[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"]] 65 - 66 66 * ((( 67 67 **Axis 1: Etiology** 68 68 69 69 * //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers. 70 70 * //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression. 71 -* //Tests//: Genetic testing, lifestyle, and cardiovascular screening. 72 - 73 - 42 +* //Tests//: Genetic testing, lifestyle and cardiovascular screening. 74 74 ))) 75 75 * ((( 76 76 **Axis 2: Molecular Markers** ... ... @@ -78,8 +78,6 @@ 78 78 * //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression. 79 79 * //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology. 80 80 * //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET). 81 - 82 - 83 83 ))) 84 84 * ((( 85 85 **Axis 3: Neuroanatomoclinical** ... ... @@ -96,12 +96,15 @@ 96 96 * **Research**: By stratifying patients, reduces cohort heterogeneity in clinical trials. 97 97 * **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking. 98 98 66 +== Who has access? == 67 + 68 +We welcome contributions from the global community. Let’s build the future of neurological diagnostics together! 69 + 99 99 == How to Contribute == 100 100 101 101 * Access the `/docs` folder for guidelines. 102 102 * Use `/code` for the latest AI pipelines. 103 103 * Share feedback and ideas in the wiki discussion pages. 104 -* Join the [[Discussion Forum at GitHub>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]] 105 105 106 106 == Key Objectives == 107 107 ... ... @@ -108,20 +108,9 @@ 108 108 * Develop interpretable AI models for diagnosis and progression tracking. 109 109 * Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources. 110 110 * Foster collaboration among neuroscientists, AI researchers, and clinicians. 111 -* Provide a dual diagnostic system: 112 -** Probabilistic Diagnosis – AI assigns multiple traditional possible diagnoses with probability percentages. 113 -** Tridimensional Diagnosis – AI structures diagnoses based on etiology, biomarkers, and neuroanatomical correlations. 114 - 115 -== Who has access? == 116 - 117 -We welcome contributions from the global community. Join us as we transform CNS diagnostics and drive precision medicine forward through a collaborative, open-source approach. Let’s build the future of neurological diagnostics together! 118 118 ))) 119 119 120 120 121 - 122 - 123 - 124 - 125 125 (% class="col-xs-12 col-sm-4" %) 126 126 ((( 127 127 {{box title="**Contents**"}} ... ... @@ -135,8 +135,6 @@ 135 135 * `/data`: Sample datasets for testing. 136 136 * `/outputs`: Generated models, visualizations, and reports. 137 137 * [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]] 138 -* [[Notebooks>>Notebooks]] 139 139 * [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]] 140 -* [[to-do-list>>to-do-list]] 141 141 ))) 142 142 )))