Attention: The EBRAINS IDM/IAM will be down tomorrow, Wednesday 17nd December, from 17:00 CET for up to 30 minutes for maintenance. Please be aware that this will affect all services that require login or authentication.


Changes for page Methodology

Last modified by manuelmenendez on 2025/03/14 08:31
From version 17.1
edited by manuelmenendez
on 2025/02/09 13:01
Change comment: There is no comment for this version
To version 12.2
edited by manuelmenendez
on 2025/02/09 09:54
Change comment: There is no comment for this version

Summary

Details

Page properties
Content
... ... @@ -1,154 +1,273 @@
1 -== **Overview** ==
1 +==== **Overview** ====
2 2  
3 -Neurodiagnoses develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility.**
3 +This project develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility**. The methodology integrates **multi-modal data**, including **genetic, neuroimaging, neurophysiological, and biomarker datasets**, and applies **machine learning models** to generate **structured, explainable diagnostic outputs**.
4 4  
5 -This methodology integrates **multi-modal data**, including:
6 -**Genetic data** (whole-genome sequencing, polygenic risk scores).
7 -**Neuroimaging** (MRI, PET, EEG, MEG).
8 -**Neurophysiological data** (EEG-based biomarkers, sleep actigraphy).
9 -**CSF & Blood Biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
5 +=== **Workflow** ===
10 10  
11 -By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
7 +1. (((
8 +**We Use GitHub to [[Store and develop AI models, scripts, and annotation pipelines.>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]**
12 12  
10 +* Create a **GitHub repository** for AI scripts and models.
11 +* Use **GitHub Projects** to manage research milestones.
12 +)))
13 +1. (((
14 +**We Use EBRAINS for Data & Collaboration**
15 +
16 +* Store **biomarker and neuroimaging data** in **EBRAINS Buckets**.
17 +* Run **Jupyter Notebooks** in **EBRAINS Lab** to test AI models.
18 +* Use **EBRAINS Wiki** for structured documentation and research discussion.
19 +)))
20 +
13 13  ----
14 14  
15 -== **Data Integration & External Databases** ==
23 +=== **1. Data Integration** ===
16 16  
17 -=== **How to Use External Databases in Neurodiagnoses** ===
25 +== Overview ==
18 18  
19 -Neurodiagnoses integrates data from multiple **biomedical and neurological research databases**. Researchers can follow these steps to **access, prepare, and integrate** data into the Neurodiagnoses framework.
20 20  
21 -**Potential Data Sources**
22 -**Reference:** [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
28 +Neurodiagnoses integrates clinical data via the **EBRAINS Medical Informatics Platform (MIP)**. MIP federates decentralized clinical data, allowing Neurodiagnoses to securely access and process sensitive information for AI-based diagnostics.
23 23  
24 -=== **Register for Access** ===
30 +== How It Works ==
25 25  
26 -Each **external database** requires **individual registration** and approval.
27 -✔️ Follow the official **data access guidelines** of each provider.
28 -✔️ Ensure compliance with **ethical approvals** and **data-sharing agreements (DUAs).**
29 29  
30 -=== **Download & Prepare Data** ===
33 +1. (((
34 +**Authentication & API Access:**
31 31  
32 -Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
36 +* Users must have an **EBRAINS account**.
37 +* Neurodiagnoses uses **secure API endpoints** to fetch clinical data (e.g., from the **Federation for Dementia**).
38 +)))
39 +1. (((
40 +**Data Mapping & Harmonization:**
33 33  
34 -**Supported File Formats**
42 +* Retrieved data is **normalized** and converted to standard formats (.csv, .json).
43 +* Data from **multiple sources** is harmonized to ensure consistency for AI processing.
44 +)))
45 +1. (((
46 +**Security & Compliance:**
35 35  
36 -* **Tabular Data**: .csv, .tsv
37 -* **Neuroimaging Data**: .nii, .dcm
38 -* **Genomic Data**: .fasta, .vcf
39 -* **Clinical Metadata**: .json, .xml
48 +* All data access is **logged and monitored**.
49 +* Data remains on **MIP servers** using **federated learning techniques** when possible.
50 +* Access is granted only after signing a **Data Usage Agreement (DUA)**.
51 +)))
40 40  
41 -**Mandatory Fields for Integration**
53 +== Implementation Steps ==
42 42  
43 -|=**Field Name**|=**Description**
44 -|**Subject ID**|Unique patient identifier
45 -|**Diagnosis**|Standardized disease classification
46 -|**Biomarkers**|CSF, plasma, or imaging biomarkers
47 -|**Genetic Data**|Whole-genome or exome sequencing
48 -|**Neuroimaging Metadata**|MRI/PET acquisition parameters
49 49  
50 -=== **Upload Data to Neurodiagnoses** ===
56 +1. Clone the repository.
57 +1. Configure your **EBRAINS API credentials** in mip_integration.py.
58 +1. Run the script to **download and harmonize clinical data**.
59 +1. Process the data for **AI model training**.
51 51  
52 -**Option 1:** Upload to **EBRAINS Bucket** → [[Neurodiagnoses Data Storage>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
53 -**Option 2:** Contribute via **GitHub Repository** → [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
61 +For more detailed instructions, please refer to the **[[MIP Documentation>>url:https://mip.ebrains.eu/]]**.
54 54  
55 -**For large datasets, please contact project administrators before uploading.**
63 +----
56 56  
57 -=== **Integrate Data into AI Models** ===
65 += Data Processing & Integration with Clinica.Run =
58 58  
59 -Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
60 -Standardize data using **harmonization tools.**
61 -Train AI models with **newly integrated datasets.**
62 62  
63 -**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
68 +== Overview ==
64 64  
65 -----
66 66  
67 -== **AI-Powered Annotation & Machine Learning Models** ==
71 +Neurodiagnoses now supports **Clinica.Run**, an open-source neuroimaging platform designed for **multimodal data processing and reproducible neuroscience workflows**.
68 68  
69 -Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
73 +== How It Works ==
70 70  
71 -=== **AI Model Categories** ===
72 72  
73 -|=**Model Type**|=**Function**|=**Example Algorithms**
74 -|**Probabilistic Diagnosis**|Assigns probability scores to multiple CNS disorders.|Random Forest, XGBoost, Bayesian Networks
75 -|**Tridimensional Diagnosis**|Classifies disorders based on Etiology, Biomarkers, and Neuroanatomical Correlations.|CNNs, Transformers, Autoencoders
76 -|**Biomarker Prediction**|Predicts missing biomarker values using regression.|KNN Imputation, Bayesian Estimation
77 -|**Neuroimaging Feature Extraction**|Extracts patterns from MRI, PET, EEG.|CNNs, Graph Neural Networks
78 -|**Clinical Decision Support**|Generates AI-driven diagnostic reports.|SHAP Explainability Tools
76 +1. (((
77 +**Neuroimaging Preprocessing:**
79 79  
80 -**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
79 +* MRI, PET, EEG data is preprocessed using **Clinica.Run pipelines**.
80 +* Supports **longitudinal and cross-sectional analyses**.
81 +)))
82 +1. (((
83 +**Automated Biomarker Extraction:**
81 81  
85 +* Standardized extraction of **volumetric, metabolic, and functional biomarkers**.
86 +* Integration with machine learning models in Neurodiagnoses.
87 +)))
88 +1. (((
89 +**Data Security & Compliance:**
90 +
91 +* Clinica.Run operates in **compliance with GDPR and HIPAA**.
92 +* Neuroimaging data remains **within the original storage environment**.
93 +)))
94 +
95 +== Implementation Steps ==
96 +
97 +
98 +1. Install **Clinica.Run** dependencies.
99 +1. Configure your **Clinica.Run pipeline** in clinica_run_config.json.
100 +1. Run the pipeline for **preprocessing and biomarker extraction**.
101 +1. Use processed neuroimaging data for **AI-driven diagnostics** in Neurodiagnoses.
102 +
103 +For further information, refer to **[[Clinica.Run Documentation>>url:https://clinica.run/]]**.
104 +
105 +==== ====
106 +
107 +==== **Data Sources** ====
108 +
109 +[[List of potential sources of databases>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
110 +
111 +**Biomedical Ontologies & Databases:**
112 +
113 +* **Human Phenotype Ontology (HPO)** for symptom annotation.
114 +* **Gene Ontology (GO)** for molecular and cellular processes.
115 +
116 +**Dimensionality Reduction and Interpretability:**
117 +
118 +* **Evaluate interpretability** using metrics like the **Area Under the Interpretability Curve (AUIC)**.
119 +* **Leverage [[DEIBO>>https://github.com/Mellandd/DEIBO]] (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
120 +
121 +**Neuroimaging & EEG/MEG Data:**
122 +
123 +* **MRI volumetric measures** for brain atrophy tracking.
124 +* **EEG functional connectivity patterns** (AI-Mind).
125 +
126 +**Clinical & Biomarker Data:**
127 +
128 +* **CSF biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
129 +* **Sleep monitoring and actigraphy data** (ADIS).
130 +
131 +**Federated Learning Integration:**
132 +
133 +* **Secure multi-center data harmonization** (PROMINENT).
134 +
82 82  ----
83 83  
84 -== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
137 +==== **Annotation System for Multi-Modal Data** ====
85 85  
86 -Neurodiagnoses generates **structured AI reports** for clinicians, combining:
139 +To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
87 87  
88 -**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
89 -**Tridimensional Classification:** Standardized diagnostic reports based on:
141 +* **Assign standardized metadata tags** to diagnostic features.
142 +* **Provide contextual explanations** for AI-based classifications.
143 +* **Track temporal disease progression annotations** to identify long-term trends.
90 90  
91 -1. **Axis 1:** **Etiology** → Genetic, Autoimmune, Prion, Toxic, Vascular.
92 -1. **Axis 2:** **Molecular Markers** → CSF, Neuroinflammation, EEG biomarkers.
93 -1. **Axis 3:** **Neuroanatomoclinical Correlations** → MRI atrophy, PET.
145 +----
94 94  
95 -**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
147 +=== **2. AI-Based Analysis** ===
96 96  
149 +==== **Machine Learning & Deep Learning Models** ====
150 +
151 +**Risk Prediction Models:**
152 +
153 +* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
154 +
155 +**Biomarker Classification & Probabilistic Imputation:**
156 +
157 +* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
158 +
159 +**Neuroimaging Feature Extraction:**
160 +
161 +* **MRI & EEG data** annotated with **neuroanatomical feature labels**.
162 +
163 +==== **AI-Powered Annotation System** ====
164 +
165 +* Uses **SHAP-based interpretability tools** to explain model decisions.
166 +* Generates **automated clinical annotations** in structured reports.
167 +* Links findings to **standardized medical ontologies** (e.g., **SNOMED, HPO**).
168 +
97 97  ----
98 98  
99 -== **Data Security, Compliance & Federated Learning** ==
171 +=== **3. Diagnostic Framework & Clinical Decision Support** ===
100 100  
101 -✔ **Privacy-Preserving AI**: Implements **Federated Learning**, ensuring that patient data **never leaves** local institutions.
102 -✔ **Secure Data Access**: Data remains **stored in EBRAINS MIP servers** using **differential privacy techniques.**
103 -✔ **Ethical & GDPR Compliance**: Data-sharing agreements **must be signed** before use.
173 +==== **Tridimensional Diagnostic Axes** ====
104 104  
105 -**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
175 +**Axis 1: Etiology (Pathogenic Mechanisms)**
106 106  
177 +* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
178 +* **AI-assisted annotation** provides **causal interpretations** for clinical use.
179 +
180 +**Axis 2: Molecular Markers & Biomarkers**
181 +
182 +* **Integration of CSF, blood, and neuroimaging biomarkers**.
183 +* **Structured annotation** highlights **biological pathways linked to diagnosis**.
184 +
185 +**Axis 3: Neuroanatomoclinical Correlations**
186 +
187 +* **MRI and EEG data** provide anatomical and functional insights.
188 +* **AI-generated progression maps** annotate **brain structure-function relationships**.
189 +
107 107  ----
108 108  
109 -== **Data Processing & Integration with Clinica.Run** ==
192 +=== **4. Computational Workflow & Annotation Pipelines** ===
110 110  
111 -Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
194 +==== **Data Processing Steps** ====
112 112  
113 -=== **How It Works** ===
196 +**Data Ingestion:**
114 114  
115 -✔ **Neuroimaging Preprocessing**: MRI, PET, EEG data is preprocessed using **Clinica.Run pipelines.**
116 -✔ **Automated Biomarker Extraction**: Extracts volumetric, metabolic, and functional biomarkers.
117 -✔ **Data Security & Compliance**: Clinica.Run is **GDPR & HIPAA-compliant.**
198 +* **Harmonized datasets** stored in **EBRAINS Bucket**.
199 +* **Preprocessing pipelines** clean and standardize data.
118 118  
119 -=== **Implementation Steps** ===
201 +**Feature Engineering:**
120 120  
121 -1. Install **Clinica.Run** dependencies.
122 -1. Configure **Clinica.Run pipeline** in clinica_run_config.json.
123 -1. Run **biomarker extraction pipelines** for AI-based diagnostics.
203 +* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
124 124  
125 -**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
205 +**AI-Generated Annotations:**
126 126  
207 +* **Automated tagging** of diagnostic features in **structured reports**.
208 +* **Explainability modules (SHAP, LIME)** ensure transparency in predictions.
209 +
210 +**Clinical Decision Support Integration:**
211 +
212 +* **AI-annotated findings** fed into **interactive dashboards**.
213 +* **Clinicians can adjust, validate, and modify annotations**.
214 +
127 127  ----
128 128  
129 -== **Collaborative Development & Research** ==
217 +=== **5. Validation & Real-World Testing** ===
130 130  
131 -**We Use GitHub to Develop AI Models & Store Research Data**
219 +==== **Prospective Clinical Study** ====
132 132  
133 -* **GitHub Repository:** AI model training scripts.
134 -* **GitHub Issues:** Tracks ongoing research questions.
135 -* **GitHub Wiki:** Project documentation & user guides.
221 +* **Multi-center validation** of AI-based **annotations & risk stratifications**.
222 +* **Benchmarking against clinician-based diagnoses**.
223 +* **Real-world testing** of AI-powered **structured reporting**.
136 136  
137 -**We Use EBRAINS for Data & Collaboration**
225 +==== **Quality Assurance & Explainability** ====
138 138  
139 -* **EBRAINS Buckets:** Large-scale neuroimaging and biomarker storage.
140 -* **EBRAINS Jupyter Notebooks:** Cloud-based AI model execution.
141 -* **EBRAINS Wiki:** Research documentation and updates.
227 +* **Annotations linked to structured knowledge graphs** for improved transparency.
228 +* **Interactive annotation editor** allows clinicians to validate AI outputs.
142 142  
143 -**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
230 +----
144 144  
232 +=== **6. Collaborative Development** ===
233 +
234 +The project is **open to contributions** from **researchers, clinicians, and developers**.
235 +
236 +**Key tools include:**
237 +
238 +* **Jupyter Notebooks**: For data analysis and pipeline development.
239 +** Example: **probabilistic imputation**
240 +* **Wiki Pages**: For documenting methods and results.
241 +* **Drive and Bucket**: For sharing code, data, and outputs.
242 +* **Collaboration with related projects**:
243 +** Example: **Beyond the hype: AI in dementia – from early risk detection to disease treatment**
244 +
145 145  ----
146 146  
147 -**For Additional Documentation:**
247 +=== **7. Tools and Technologies** ===
148 148  
149 -* **GitHub Repository:** [[Neurodiagnoses AI Models>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
150 -* **EBRAINS Wiki:** [[Neurodiagnoses Research Collaboration>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
249 +==== **Programming Languages:** ====
151 151  
251 +* **Python** for AI and data processing.
252 +
253 +==== **Frameworks:** ====
254 +
255 +* **TensorFlow** and **PyTorch** for machine learning.
256 +* **Flask** or **FastAPI** for backend services.
257 +
258 +==== **Visualization:** ====
259 +
260 +* **Plotly** and **Matplotlib** for interactive and static visualizations.
261 +
262 +==== **EBRAINS Services:** ====
263 +
264 +* **Collaboratory Lab** for running Notebooks.
265 +* **Buckets** for storing large datasets.
266 +
152 152  ----
153 153  
154 -**Neurodiagnoses is Open for Contributions – Join Us Today!**
269 +=== **Why This Matters** ===
270 +
271 +* The annotation system ensures that AI-generated insights are structured, interpretable, and clinically meaningful.
272 +* It enables real-time tracking of disease progression across the three diagnostic axes.
273 +* It facilitates integration with electronic health records and decision-support tools, improving AI adoption in clinical workflows.