Changes for page Neurodiagnoses
Last modified by manuelmenendez on 2025/03/03 22:46
From version 46.1
edited by manuelmenendez
on 2025/02/19 18:57
on 2025/02/19 18:57
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To version 23.1
edited by manuelmenendez
on 2025/01/29 18:46
on 2025/01/29 18:46
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... ... @@ -2,9 +2,9 @@ 2 2 ((( 3 3 (% class="container" %) 4 4 ((( 5 -= //A new tridimensional diagnostic framework for complexCNS diseases// =5 += //A new tridimensional diagnostic framework for CNS diseases// = 6 6 7 -This project is focused on developing a novel nosological and diagnostic framework for complexCNS diseases 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 CNS 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 ))) ... ... @@ -15,54 +15,27 @@ 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 CNS diseases can be classified and diagnosed 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 - In additionto these clinical diagnosticapproaches,Neurodiagnoseshasexpanded intoa 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 +[[For instance, 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 -To enhance standardization, interpretability, and clinical application, the framework integrates an AI-powered annotation system, which: 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 60 == **The case of neurodegenerative diseases** == 61 61 62 62 There have been described these 3 diagnostic axes: 63 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 ... ... @@ -69,8 +69,6 @@ 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 71 * //Tests//: Genetic testing, lifestyle, and cardiovascular screening. 72 - 73 - 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** ... ... @@ -96,13 +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 68 +== Who has access? == 69 + 70 +We welcome contributions from the global community. Let’s build the future of neurological diagnostics together! 71 + 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 our [[Community on EBRAINS>>https://community.ebrains.eu/_ideas/-OJHTZrpKrrrkx-u0djj/about]] 105 -* Join the [[Discussion Forum at GitHub>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]] 106 106 107 107 == Key Objectives == 108 108 ... ... @@ -109,20 +109,9 @@ 109 109 * Develop interpretable AI models for diagnosis and progression tracking. 110 110 * Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources. 111 111 * Foster collaboration among neuroscientists, AI researchers, and clinicians. 112 -* Provide a dual diagnostic system: 113 -** Probabilistic Diagnosis – AI assigns multiple traditional possible diagnoses with probability percentages. 114 -** Tridimensional Diagnosis – AI structures diagnoses based on etiology, biomarkers, and neuroanatomical correlations. 115 - 116 -== Who has access? == 117 - 118 -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! 119 119 ))) 120 120 121 121 122 - 123 - 124 - 125 - 126 126 (% class="col-xs-12 col-sm-4" %) 127 127 ((( 128 128 {{box title="**Contents**"}} ... ... @@ -136,7 +136,6 @@ 136 136 * `/data`: Sample datasets for testing. 137 137 * `/outputs`: Generated models, visualizations, and reports. 138 138 * [[Methodology>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Methodology/]] 139 -* [[Notebooks>>Notebooks]] 140 140 * [[Results>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Results/]] 141 141 * [[to-do-list>>to-do-list]] 142 142 )))