Changes for page Neurodiagnoses
Last modified by manuelmenendez on 2025/03/03 22:46
From version 35.1
edited by manuelmenendez
on 2025/02/02 00:48
on 2025/02/02 00:48
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To version 41.1
edited by manuelmenendez
on 2025/02/02 15:13
on 2025/02/02 15:13
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... ... @@ -2,9 +2,9 @@ 2 2 ((( 3 3 (% class="container" %) 4 4 ((( 5 -= //A new tridimensional diagnostic framework for CNS diseases// = 5 += //A new tridimensional diagnostic framework for complex CNS diseases// = 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. 7 +This project is focused on developing a novel nosological and diagnostic framework for complex 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 ))) ... ... @@ -18,16 +18,10 @@ 18 18 = **Overview** = 19 19 20 20 21 -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.21 +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. 22 22 23 - This project proposes a**new diagnosticframework**—onethat **shifts from symptom-based classifications**to an**etiology-driven,tridimensionalsystem**.Byintegrating**genetics,proteomics,neuroimaging,computationalmodeling,andAI-powered annotations**,this approach aimstoprovide**moreprecise,scalable, andbiologicallygrounded methodfordiagnosingandmanagingCNS diseases**.23 +Neurodiagnoses is an open-source AI-powered diagnostic system designed for complex CNS disorders, including neurodegenerative diseases, autoimmune encephalopathies, prion disorders, and genetic syndromes. 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. 24 24 25 -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**. 26 - 27 -=== **Project Aim** === 28 - 29 -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**. 30 - 31 31 The //Tridimensional Diagnostic Framework// redefines CNS diseases can be classified and diagnosed by focusing on: 32 32 33 33 * **Axis 1**: Etiology (genetic or other causes of diseases). ... ... @@ -40,16 +40,38 @@ 40 40 * Integration of incomplete datasets using AI-driven probabilistic modeling. 41 41 * Stratification of patients for personalized treatment. 42 42 43 -== **The Role of AI-PoweredAnnotation** ==37 +== **The role of AI-powered annotation** == 44 44 45 -To enhance **standardization, interpretability, and clinical application**, the framework integrates**an AI-powered annotation system**, which:39 +To enhance standardization, interpretability, and clinical application, the framework integrates an AI-powered annotation system, which: 46 46 47 -* **Assigns structured metadata tags**to diagnostic features.48 -* **Provides real-time contextual explanations**for AI-based classifications.49 -* **Tracks longitudinal disease progression**using timestamped AI annotations.50 -* **Improves AI model transparency**through interpretability tools (e.g., SHAP analysis).51 -* **Facilitates decision-making for clinicians**by linking annotations to standardized biomedical ontologies (SNOMED, HPO).41 +* Assigns structured metadata tags to diagnostic features. 42 +* Provides real-time contextual explanations for AI-based classifications. 43 +* Tracks longitudinal disease progression using timestamped AI annotations. 44 +* Improves AI model transparency through interpretability tools (e.g., SHAP analysis). 45 +* Facilitates decision-making for clinicians by linking annotations to standardized biomedical ontologies (SNOMED, HPO). 52 52 47 +Neurodiagnoses provides two complementary AI-driven diagnostic approaches: 48 + 49 +1. Traditional Probabilistic Diagnosis 50 + 51 +* AI provides multiple possible diagnoses, each assigned a probability percentage based on biomarker, imaging, and clinical data. 52 +* Example Output: 53 +** 75% Alzheimer's Disease 54 +** 20% Lewy Body Dementia 55 +** 5% Vascular Dementia 56 +* Useful for differential diagnosis and treatment decision-making. 57 + 58 +2. Tridimensional Diagnosis 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. 65 + 66 +For every patient case, both systems will be offered, allowing clinicians to compare AI-generated probabilistic diagnosis with a structured tridimensional classification. 67 + 68 + 53 53 == **The case of neurodegenerative diseases** == 54 54 55 55 There have been described these 3 diagnostic axes: ... ... @@ -62,6 +62,8 @@ 62 62 * //Description//: Focuses on genetic and sporadic causes, identifying risk factors and potential triggers. 63 63 * //Examples//: APOE ε4 as a genetic risk factor, or cardiovascular health affecting NDD progression. 64 64 * //Tests//: Genetic testing, lifestyle, and cardiovascular screening. 81 + 82 + 65 65 ))) 66 66 * ((( 67 67 **Axis 2: Molecular Markers** ... ... @@ -69,6 +69,8 @@ 69 69 * //Description//: Analyzes primary (amyloid-beta, tau) and secondary biomarkers (NFL, GFAP) for tracking disease progression. 70 70 * //Examples//: CSF amyloid-beta concentrations to confirm Alzheimer’s pathology. 71 71 * //Tests//: Blood/CSF biomarkers, PET imaging (Tau-PET, Amyloid-PET). 90 + 91 + 72 72 ))) 73 73 * ((( 74 74 **Axis 3: Neuroanatomoclinical**