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Changes for page Methodology

Last modified by manuelmenendez on 2025/03/14 08:31
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edited by manuelmenendez
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To version 17.1
edited by manuelmenendez
on 2025/02/09 13:01
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Summary

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1 1  == **Overview** ==
2 2  
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**.
3 +Neurodiagnoses develops a **tridimensional diagnostic framework** for **CNS diseases**, incorporating **AI-powered annotation tools** to improve **interpretability, standardization, and clinical utility.**
4 4  
5 -== **Workflow** ==
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).
6 6  
7 -1. (((
8 -**We Use GitHub to [[Store and develop AI models, scripts, and annotation pipelines.>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]**
11 +By applying **machine learning models**, Neurodiagnoses generates **structured, explainable diagnostic outputs** to assist **clinical decision-making** and **biomarker-driven patient stratification.**
9 9  
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 -
21 21  ----
22 22  
23 -== **1. Data Integration** ==
15 +== **Data Integration & External Databases** ==
24 24  
25 -=== **EBRAINS Medical Informatics Platform (MIP)**. ===
17 +=== **How to Use External Databases in Neurodiagnoses** ===
26 26  
27 -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.
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.
28 28  
29 -==== How It Works ====
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]]
30 30  
24 +=== **Register for Access** ===
31 31  
32 -1. (((
33 -**Authentication & API Access:**
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).**
34 34  
35 -* Users must have an **EBRAINS account**.
36 -* Neurodiagnoses uses **secure API endpoints** to fetch clinical data (e.g., from the **Federation for Dementia**).
37 -)))
38 -1. (((
39 -**Data Mapping & Harmonization:**
30 +=== **Download & Prepare Data** ===
40 40  
41 -* Retrieved data is **normalized** and converted to standard formats (.csv, .json).
42 -* Data from **multiple sources** is harmonized to ensure consistency for AI processing.
43 -)))
44 -1. (((
45 -**Security & Compliance:**
32 +Once access is granted, download datasets **following compliance guidelines** and **format requirements** for integration.
46 46  
47 -* All data access is **logged and monitored**.
48 -* Data remains on **MIP servers** using **federated learning techniques** when possible.
49 -* Access is granted only after signing a **Data Usage Agreement (DUA)**.
50 -)))
34 +**Supported File Formats**
51 51  
52 -==== Implementation Steps ====
36 +* **Tabular Data**: .csv, .tsv
37 +* **Neuroimaging Data**: .nii, .dcm
38 +* **Genomic Data**: .fasta, .vcf
39 +* **Clinical Metadata**: .json, .xml
53 53  
41 +**Mandatory Fields for Integration**
54 54  
55 -1. Clone the repository.
56 -1. Configure your **EBRAINS API credentials** in mip_integration.py.
57 -1. Run the script to **download and harmonize clinical data**.
58 -1. Process the data for **AI model training**.
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
59 59  
60 -For more detailed instructions, please refer to the **[[MIP Documentation>>url:https://mip.ebrains.eu/]]**.
50 +=== **Upload Data to Neurodiagnoses** ===
61 61  
62 -----
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]]
63 63  
64 -=== Data Processing & Integration with Clinica.Run ===
55 +**For large datasets, please contact project administrators before uploading.**
65 65  
66 -Neurodiagnoses now supports **Clinica.Run**, an open-source neuroimaging platform designed for **multimodal data processing and reproducible neuroscience workflows**.
57 +=== **Integrate Data into AI Models** ===
67 67  
68 -==== How It Works ====
59 +Use **Jupyter Notebooks** on EBRAINS for **data preprocessing.**
60 +Standardize data using **harmonization tools.**
61 +Train AI models with **newly integrated datasets.**
69 69  
63 +**Reference:** [[Data Processing Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]]
70 70  
71 -1. (((
72 -**Neuroimaging Preprocessing:**
65 +----
73 73  
74 -* MRI, PET, EEG data is preprocessed using **Clinica.Run pipelines**.
75 -* Supports **longitudinal and cross-sectional analyses**.
76 -)))
77 -1. (((
78 -**Automated Biomarker Extraction:**
67 +== **AI-Powered Annotation & Machine Learning Models** ==
79 79  
80 -* Standardized extraction of **volumetric, metabolic, and functional biomarkers**.
81 -* Integration with machine learning models in Neurodiagnoses.
82 -)))
83 -1. (((
84 -**Data Security & Compliance:**
69 +Neurodiagnoses applies **advanced machine learning models** to classify CNS diseases, extract features from **biomarkers and neuroimaging**, and provide **AI-powered annotation.**
85 85  
86 -* Clinica.Run operates in **compliance with GDPR and HIPAA**.
87 -* Neuroimaging data remains **within the original storage environment**.
88 -)))
71 +=== **AI Model Categories** ===
89 89  
90 -==== Implementation Steps ====
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
91 91  
80 +**Reference:** [[AI Model Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/models.md]]
92 92  
93 -1. Install **Clinica.Run** dependencies.
94 -1. Configure your **Clinica.Run pipeline** in clinica_run_config.json.
95 -1. Run the pipeline for **preprocessing and biomarker extraction**.
96 -1. Use processed neuroimaging data for **AI-driven diagnostics** in Neurodiagnoses.
82 +----
97 97  
98 -For further information, refer to **[[Clinica.Run Documentation>>url:https://clinica.run/]]**.
84 +== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
99 99  
100 -==== ====
86 +Neurodiagnoses generates **structured AI reports** for clinicians, combining:
101 101  
102 -==== **Data Sources** ====
88 +**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
89 +**Tridimensional Classification:** Standardized diagnostic reports based on:
103 103  
104 -[[List of potential sources of databases>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
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.
105 105  
106 -**Biomedical Ontologies & Databases:**
95 +**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
107 107  
108 -* **Human Phenotype Ontology (HPO)** for symptom annotation.
109 -* **Gene Ontology (GO)** for molecular and cellular processes.
110 -
111 -**Dimensionality Reduction and Interpretability:**
112 -
113 -* **Evaluate interpretability** using metrics like the **Area Under the Interpretability Curve (AUIC)**.
114 -* **Leverage [[DEIBO>>https://github.com/Mellandd/DEIBO]] (Data-driven Embedding Interpretation Based on Ontologies)** to connect model dimensions to ontology concepts.
115 -
116 -**Neuroimaging & EEG/MEG Data:**
117 -
118 -* **MRI volumetric measures** for brain atrophy tracking.
119 -* **EEG functional connectivity patterns** (AI-Mind).
120 -
121 -**Clinical & Biomarker Data:**
122 -
123 -* **CSF biomarkers** (Amyloid-beta, Tau, Neurofilament Light).
124 -* **Sleep monitoring and actigraphy data** (ADIS).
125 -
126 -**Federated Learning Integration:**
127 -
128 -* **Secure multi-center data harmonization** (PROMINENT).
129 -
130 130  ----
131 131  
132 -==== **Annotation System for Multi-Modal Data** ====
99 +== **Data Security, Compliance & Federated Learning** ==
133 133  
134 -To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
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.
135 135  
136 -* **Assign standardized metadata tags** to diagnostic features.
137 -* **Provide contextual explanations** for AI-based classifications.
138 -* **Track temporal disease progression annotations** to identify long-term trends.
105 +**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
139 139  
140 140  ----
141 141  
142 -== **2. AI-Based Analysis** ==
109 +== **Data Processing & Integration with Clinica.Run** ==
143 143  
144 -==== **Machine Learning & Deep Learning Models** ====
111 +Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
145 145  
146 -**Risk Prediction Models:**
113 +=== **How It Works** ===
147 147  
148 -* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
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.**
149 149  
150 -**Biomarker Classification & Probabilistic Imputation:**
119 +=== **Implementation Steps** ===
151 151  
152 -* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
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.
153 153  
154 -**Neuroimaging Feature Extraction:**
125 +**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
155 155  
156 -* **MRI & EEG data** annotated with **neuroanatomical feature labels**.
157 -
158 -==== **AI-Powered Annotation System** ====
159 -
160 -* Uses **SHAP-based interpretability tools** to explain model decisions.
161 -* Generates **automated clinical annotations** in structured reports.
162 -* Links findings to **standardized medical ontologies** (e.g., **SNOMED, HPO**).
163 -
164 164  ----
165 165  
166 -== **3. Diagnostic Framework & Clinical Decision Support** ==
129 +== **Collaborative Development & Research** ==
167 167  
168 -==== **Tridimensional Diagnostic Axes** ====
131 +**We Use GitHub to Develop AI Models & Store Research Data**
169 169  
170 -**Axis 1: Etiology (Pathogenic Mechanisms)**
133 +* **GitHub Repository:** AI model training scripts.
134 +* **GitHub Issues:** Tracks ongoing research questions.
135 +* **GitHub Wiki:** Project documentation & user guides.
171 171  
172 -* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
173 -* **AI-assisted annotation** provides **causal interpretations** for clinical use.
137 +**We Use EBRAINS for Data & Collaboration**
174 174  
175 -**Axis 2: Molecular Markers & Biomarkers**
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.
176 176  
177 -* **Integration of CSF, blood, and neuroimaging biomarkers**.
178 -* **Structured annotation** highlights **biological pathways linked to diagnosis**.
143 +**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
179 179  
180 -**Axis 3: Neuroanatomoclinical Correlations**
181 -
182 -* **MRI and EEG data** provide anatomical and functional insights.
183 -* **AI-generated progression maps** annotate **brain structure-function relationships**.
184 -
185 185  ----
186 186  
187 -== **4. Computational Workflow & Annotation Pipelines** ==
147 +**For Additional Documentation:**
188 188  
189 -==== **Data Processing Steps** ====
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/]]
190 190  
191 -**Data Ingestion:**
192 -
193 -* **Harmonized datasets** stored in **EBRAINS Bucket**.
194 -* **Preprocessing pipelines** clean and standardize data.
195 -
196 -**Feature Engineering:**
197 -
198 -* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
199 -
200 -**AI-Generated Annotations:**
201 -
202 -* **Automated tagging** of diagnostic features in **structured reports**.
203 -* **Explainability modules (SHAP, LIME)** ensure transparency in predictions.
204 -
205 -**Clinical Decision Support Integration:**
206 -
207 -* **AI-annotated findings** fed into **interactive dashboards**.
208 -* **Clinicians can adjust, validate, and modify annotations**.
209 -
210 210  ----
211 211  
212 -== **5. Validation & Real-World Testing** ==
213 -
214 -==== **Prospective Clinical Study** ====
215 -
216 -* **Multi-center validation** of AI-based **annotations & risk stratifications**.
217 -* **Benchmarking against clinician-based diagnoses**.
218 -* **Real-world testing** of AI-powered **structured reporting**.
219 -
220 -==== **Quality Assurance & Explainability** ====
221 -
222 -* **Annotations linked to structured knowledge graphs** for improved transparency.
223 -* **Interactive annotation editor** allows clinicians to validate AI outputs.
224 -
225 -----
226 -
227 -== **6. Collaborative Development** ==
228 -
229 -The project is **open to contributions** from **researchers, clinicians, and developers**.
230 -
231 -**Key tools include:**
232 -
233 -* **Jupyter Notebooks**: For data analysis and pipeline development.
234 -** Example: **probabilistic imputation**
235 -* **Wiki Pages**: For documenting methods and results.
236 -* **Drive and Bucket**: For sharing code, data, and outputs.
237 -* **Collaboration with related projects**:
238 -** Example: **Beyond the hype: AI in dementia – from early risk detection to disease treatment**
239 -
240 -----
241 -
242 -== **7. Tools and Technologies** ==
243 -
244 -==== **Programming Languages:** ====
245 -
246 -* **Python** for AI and data processing.
247 -
248 -==== **Frameworks:** ====
249 -
250 -* **TensorFlow** and **PyTorch** for machine learning.
251 -* **Flask** or **FastAPI** for backend services.
252 -
253 -==== **Visualization:** ====
254 -
255 -* **Plotly** and **Matplotlib** for interactive and static visualizations.
256 -
257 -==== **EBRAINS Services:** ====
258 -
259 -* **Collaboratory Lab** for running Notebooks.
260 -* **Buckets** for storing large datasets.
154 +**Neurodiagnoses is Open for Contributions – Join Us Today!**