Changes for page Neurodiagnoses
Last modified by manuelmenendez on 2025/03/03 22:46
From version 40.1
edited by manuelmenendez
on 2025/02/02 15:12
on 2025/02/02 15:12
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To version 47.1
edited by manuelmenendez
on 2025/03/03 22:46
on 2025/03/03 22:46
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... ... @@ -17,25 +17,21 @@ 17 17 18 18 = **Overview** = 19 19 20 +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. 20 20 21 - Theclassification anddiagnosisof central nervoussystem (CNS) diseaseshavelong been constrainedby traditionalphenotype-basedpproaches,whichoften failcapture the complexpathophysiologicalmechanisms,molecular biomarkers, andneuroanatomicalchangesthatseaseprogression.22 +**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 22 23 -Neurodiagnoses is anpen-source AI-powereddiagnostic system designed for complexCNS disorders, including neurodegenerativediseases,autoimmuneencephalopathies, priondisorders,andgenetic syndromes. The projectaims to develop a tridimensional diagnostic framework withan AI-powered annotationsystem, integratingetiology, molecularbiomarkers,and neuroanatomoclinicalcorrelationsforprecise, standardized,andscalable CNSdiseasediagnostics.24 +Additionally, **Neurodiagnoses is now expanding into disease prediction and biomarker estimation**, integrating state-of-the-art machine learning models to enhance precision diagnostics and disease progression forecasting. 24 24 25 - The //TridimensionalDiagnostic Framework// redefinesCNS diseases can be classified and diagnosedbyfocusingon:26 +On this page, you will find: 26 26 27 -* **Axis 1**: Etiology (genetic or other causes of diseases). 28 -* **Axis 2**: Molecular Markers (biomarkers). 29 -* **Axis 3**: Neuroanatomoclinical correlations (linking clinical symptoms to structural changes in the nervous system). 28 +* Detailed descriptions of both the clinical diagnostic tools and the research framework. 29 +* Access to our AI models, data processing pipelines, and digital twin simulations. 30 +* Collaborative resources for researchers, clinicians, and AI developers. 31 +* Guidelines and instructions on how to contribute to and expand the project. 30 30 31 -Th is methodologyenables:33 +== **The role of AI-powered annotation** == 32 32 33 -* Greater precision in diagnosis. 34 -* Integration of incomplete datasets using AI-driven probabilistic modeling. 35 -* Stratification of patients for personalized treatment. 36 - 37 -== **The Role of AI-Powered Annotation** == 38 - 39 39 To enhance standardization, interpretability, and clinical application, the framework integrates an AI-powered annotation system, which: 40 40 41 41 * Assigns structured metadata tags to diagnostic features. ... ... @@ -44,28 +44,34 @@ 44 44 * Improves AI model transparency through interpretability tools (e.g., SHAP analysis). 45 45 * Facilitates decision-making for clinicians by linking annotations to standardized biomedical ontologies (SNOMED, HPO). 46 46 47 -Neurodiagnoses provides two complementary AI-driven diagnostic approaches: 43 +Neurodiagnoses provides **two complementary AI-driven diagnostic approaches**: 48 48 49 -1. Traditional Probabilistic Diagnosis 45 +1. **Probabilistic Diagnosis** 46 + * AI assigns probability scores to multiple possible diagnoses based on biomarker, imaging, and clinical data. 47 + * Useful for differential diagnosis and treatment decision-making. 50 50 51 - *AI provides multiplepossiblediagnoses, each assigned a probability percentage basedonbiomarker, imaging, and clinical data.52 -* ExampleOutput:53 -** 75% Alzheimer'sDisease54 -** 0%LewyBody Dementia55 -** 5% VascularDementia56 -* Usefulfordifferential diagnosis andtreatmentdecision-making.49 +2. **Tridimensional Diagnosis** 50 + * Diagnoses are structured based on: 51 + - **(1) Etiology** (genetic, autoimmune, metabolic, infectious). 52 + - **(2) Molecular Biomarkers** (amyloid-beta, tau, inflammatory markers, EEG patterns). 53 + - **(3) Neuroanatomoclinical Correlations** (brain atrophy, connectivity alterations). 54 + * This approach enables precise disease subtyping and biologically meaningful classification, particularly useful for tracking progression over time. 57 57 58 - 2. TridimensionalDiagnosis56 +Both systems will be offered for every patient case, allowing clinicians to compare AI-generated probabilistic diagnosis with a structured tridimensional classification. 59 59 60 -* Diagnoses are structured based on: 61 -(1) Etiology (genetic, autoimmune, metabolic, infectious) 62 -(2) Molecular Biomarkers (amyloid-beta, tau, inflammatory markers, EEG patterns) 63 -(3) Neuroanatomoclinical Correlations (brain atrophy, connectivity alterations) 64 -* This approach enables precise disease subtyping and biologically meaningful classification, particularly useful to track progression over time. 58 +== **Disease Prediction and Biomarker Estimation** == 65 65 66 - Forevery patient case, bothsystemswillbe offered,allowingclinicianstocompareAI-generatedprobabilisticdiagnosiswithastructuredtridimensionalclassification.60 +Neurodiagnoses is also implementing **biomarker prediction and disease progression modeling**, using advanced machine learning techniques: 67 67 62 +* **Biomarker Prediction:** 63 + - Estimation of fluid-based and neuroimaging biomarkers without invasive testing. 64 + - Multi-modal machine learning models for predicting molecular and clinical markers. 68 68 66 +* **Disease Progression Modeling:** 67 + - AI-driven forecasts for neurodegenerative disease evolution. 68 + - Probabilistic disease conversion models (e.g., MCI to AD, Parkinson's prodromal phases). 69 + - Survival models and risk stratification for precision medicine applications. 70 + 69 69 == **The case of neurodegenerative diseases** == 70 70 71 71 There have been described these 3 diagnostic axes: ... ... @@ -74,25 +74,18 @@ 74 74 75 75 * ((( 76 76 **Axis 1: Etiology** 77 - 78 78 * //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers. 79 79 * //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression. 80 80 * //Tests//: Genetic testing, lifestyle, and cardiovascular screening. 81 - 82 - 83 83 ))) 84 84 * ((( 85 85 **Axis 2: Molecular Markers** 86 - 87 87 * //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression. 88 88 * //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology. 89 89 * //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET). 90 - 91 - 92 92 ))) 93 93 * ((( 94 94 **Axis 3: Neuroanatomoclinical** 95 - 96 96 * //Description//: Links clinical symptoms to neuroanatomical changes, such as atrophy or functional impairments. 97 97 * //Examples//: Hippocampal atrophy correlating with memory deficits. 98 98 * //Tests//: MRI volumetrics, FDG-PET, neuropsychological evaluations. ... ... @@ -102,7 +102,7 @@ 102 102 103 103 This system enhances: 104 104 105 -* **Research**: By stratifying patients, reduc escohort heterogeneity in clinical trials.100 +* **Research**: By stratifying patients, reducing cohort heterogeneity in clinical trials. 106 106 * **Clinical Practice**: Provides dynamic diagnostic annotations with timestamps for longitudinal tracking. 107 107 108 108 == How to Contribute == ... ... @@ -110,6 +110,8 @@ 110 110 * Access the `/docs` folder for guidelines. 111 111 * Use `/code` for the latest AI pipelines. 112 112 * Share feedback and ideas in the wiki discussion pages. 108 +* Join our [[Community on EBRAINS>>https://community.ebrains.eu/_ideas/-OJHTZrpKrrrkx-u0djj/about]] 109 +* Join the [[Discussion Forum at GitHub>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]] 113 113 114 114 == Key Objectives == 115 115 ... ... @@ -116,17 +116,17 @@ 116 116 * Develop interpretable AI models for diagnosis and progression tracking. 117 117 * Integrate data from Human Phenotype Ontology (HPO), Gene Ontology (GO), and other biomedical resources. 118 118 * Foster collaboration among neuroscientists, AI researchers, and clinicians. 116 +* Provide a dual diagnostic system: 117 + ** Probabilistic Diagnosis – AI assigns multiple traditional possible diagnoses with probability percentages. 118 + ** Tridimensional Diagnosis – AI structures diagnoses based on etiology, biomarkers, and neuroanatomical correlations. 119 +* Implement disease prediction models for neurodegenerative conditions. 120 +* Predict biomarkers from non-invasive data sources. 119 119 120 120 == Who has access? == 121 121 122 -We welcome contributions from the global community. Let’s build the future of neurological diagnostics together! 124 +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! 123 123 ))) 124 124 125 - 126 - 127 - 128 - 129 - 130 130 (% class="col-xs-12 col-sm-4" %) 131 131 ((( 132 132 {{box title="**Contents**"}} ... ... @@ -145,3 +145,4 @@ 145 145 * [[to-do-list>>to-do-list]] 146 146 ))) 147 147 ))) 145 +