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Changes for page Methodology

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Summary

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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. 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 +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 +=== **Workflow** ===
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]]**
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 +
5 5  ----
6 6  
7 -== **How to Use External Databases in Neurodiagnoses** ==
23 +=== **1. Data Integration** ===
8 8  
9 -To enhance the accuracy of our diagnostic models, Neurodiagnoses integrates data from multiple biomedical and neurological research databases. If you are a researcher, follow these steps to access, prepare, and integrate data into the Neurodiagnoses framework.
25 +== Overview ==
10 10  
11 -=== **Potential Data Sources** ===
12 12  
13 -Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
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.
14 14  
15 -* Reference: [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
30 +== How It Works ==
16 16  
17 -=== **1. Register for Access** ===
18 18  
19 -Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
33 +1. (((
34 +**Authentication & API Access:**
20 20  
21 -* Ensure that you have completed all ethical approvals and data access agreements before integrating datasets into Neurodiagnoses.
22 -* Some repositories require a Data Usage Agreement (DUA) before downloading sensitive medical data.
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:**
23 23  
24 -=== **2. Download & Prepare Data** ===
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:**
25 25  
26 -Once access is granted, download datasets while complying with data usage policies. Ensure that the files meet Neurodiagnoses’ format requirements for smooth integration.
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 +)))
27 27  
28 -==== **Supported File Formats** ====
53 +== Implementation Steps ==
29 29  
30 -* Tabular Data: .csv, .tsv
31 -* Neuroimaging Data: .nii, .dcm
32 -* Genomic Data: .fasta, .vcf
33 -* Clinical Metadata: .json, .xml
34 34  
35 -==== **Mandatory Fields for Integration** ====
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**.
36 36  
37 -|=Field Name|=Description
38 -|Subject ID|Unique patient identifier
39 -|Diagnosis|Standardized disease classification
40 -|Biomarkers|CSF, plasma, or imaging biomarkers
41 -|Genetic Data|Whole-genome or exome sequencing
42 -|Neuroimaging Metadata|MRI/PET acquisition parameters
61 +For more detailed instructions, please refer to the **[[MIP Documentation>>url:https://mip.ebrains.eu/]]**.
43 43  
44 -=== **3. Upload Data to Neurodiagnoses** ===
63 +----
45 45  
46 -Once preprocessed, data can be uploaded to EBRAINS or GitHub.
65 += Data Processing & Integration with Clinica.Run =
47 47  
48 -* (((
49 -**Option 1: Upload to EBRAINS Bucket**
50 50  
51 -* Location: [[EBRAINS Neurodiagnoses Bucket>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
52 -* Ensure correct metadata tagging before submission.
68 +== Overview ==
69 +
70 +
71 +Neurodiagnoses now supports **Clinica.Run**, an open-source neuroimaging platform designed for **multimodal data processing and reproducible neuroscience workflows**.
72 +
73 +== How It Works ==
74 +
75 +
76 +1. (((
77 +**Neuroimaging Preprocessing:**
78 +
79 +* MRI, PET, EEG data is preprocessed using **Clinica.Run pipelines**.
80 +* Supports **longitudinal and cross-sectional analyses**.
53 53  )))
54 -* (((
55 -**Option 2: Contribute via GitHub Repository**
82 +1. (((
83 +**Automated Biomarker Extraction:**
56 56  
57 -* Location: [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
58 -* Create a new folder under /data/ and include dataset description.
85 +* Standardized extraction of **volumetric, metabolic, and functional biomarkers**.
86 +* Integration with machine learning models in Neurodiagnoses.
59 59  )))
88 +1. (((
89 +**Data Security & Compliance:**
60 60  
61 -//Note: For large datasets, please contact the project administrators before uploading.//
91 +* Clinica.Run operates in **compliance with GDPR and HIPAA**.
92 +* Neuroimaging data remains **within the original storage environment**.
93 +)))
62 62  
63 -=== **4. Integrate Data into AI Models** ===
95 +== Implementation Steps ==
64 64  
65 -Once uploaded, datasets must be harmonized and formatted before AI model training.
66 66  
67 -==== **Steps for Data Integration** ====
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.
68 68  
69 -* Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
70 -* Standardize neuroimaging and biomarker formats using harmonization tools.
71 -* Use machine learning models to handle missing data and feature extraction.
72 -* Train AI models with newly integrated patient cohorts.
73 -* Reference: [[Detailed instructions can be found in docs/data_processing.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_processing.md]].
103 +For further information, refer to **[[Clinica.Run Documentation>>url:https://clinica.run/]]**.
74 74  
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 +
75 75  ----
76 76  
77 -== **Database Sources Table** ==
137 +==== **Annotation System for Multi-Modal Data** ====
78 78  
79 -=== **Where to Insert This** ===
139 +To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
80 80  
81 -* GitHub: [[docs/data_sources.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_sources.md]]
82 -* EBRAINS Wiki: Collabs/neurodiagnoses/Data Sources
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.
83 83  
84 -=== **Key Databases for Neurodiagnoses** ===
145 +----
85 85  
86 -|=Database|=Focus Area|=Data Type|=Access Link
87 -|ADNI|Alzheimer's Disease|MRI, PET, CSF, cognitive tests|ADNI
88 -|PPMI|Parkinson’s Disease|Imaging, biospecimens|[[PPMI>>url:https://www.ppmi-info.org/]]
89 -|GP2|Genetic Data for PD|Whole-genome sequencing|[[GP2>>url:https://gp2.org/]]
90 -|Enroll-HD|Huntington’s Disease|Clinical, genetic, imaging|[[Enroll-HD>>url:https://enroll-hd.org/]]
91 -|GAAIN|Alzheimer's & Cognitive Decline|Multi-source data aggregation|[[GAAIN>>url:https://www.gaain.org/]]
92 -|UK Biobank|Population-wide studies|Genetic, imaging, health records|[[UK Biobank>>url:https://www.ukbiobank.ac.uk/]]
93 -|DPUK|Dementia & Aging|Imaging, genetics, lifestyle factors|[[DPUK>>url:https://www.dementiasplatform.uk/]]
94 -|PRION Registry|Prion Diseases|Clinical and genetic data|[[PRION Registry>>url:https://www.prionalliance.org/]]
95 -|DECIPHER|Rare Genetic Disorders|Genomic variants|DECIPHER
147 +=== **2. AI-Based Analysis** ===
96 96  
97 -If you know a relevant dataset, submit a proposal in [[GitHub Issues>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]].
149 +==== **Machine Learning & Deep Learning Models** ====
98 98  
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 +
99 99  ----
100 100  
101 -== **Collaboration & Partnerships** ==
171 +=== **3. Diagnostic Framework & Clinical Decision Support** ===
102 102  
103 -=== **Where to Insert This** ===
173 +==== **Tridimensional Diagnostic Axes** ====
104 104  
105 -* GitHub: [[docs/collaboration.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/collaboration.md]]
106 -* EBRAINS Wiki: Collabs/neurodiagnoses/Collaborations
175 +**Axis 1: Etiology (Pathogenic Mechanisms)**
107 107  
108 -=== **Partnering with Data Providers** ===
177 +* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
178 +* **AI-assisted annotation** provides **causal interpretations** for clinical use.
109 109  
110 -Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
180 +**Axis 2: Molecular Markers & Biomarkers**
111 111  
112 -* Enable direct API-based data integration for real-time processing.
113 -* Co-develop harmonized AI-ready datasets with standardized annotations.
114 -* Secure funding opportunities through joint grant applications.
182 +* **Integration of CSF, blood, and neuroimaging biomarkers**.
183 +* **Structured annotation** highlights **biological pathways linked to diagnosis**.
115 115  
116 -=== **Interested in Partnering?** ===
185 +**Axis 3: Neuroanatomoclinical Correlations**
117 117  
118 -If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
187 +* **MRI and EEG data** provide anatomical and functional insights.
188 +* **AI-generated progression maps** annotate **brain structure-function relationships**.
119 119  
120 -* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
190 +----
121 121  
192 +=== **4. Computational Workflow & Annotation Pipelines** ===
193 +
194 +==== **Data Processing Steps** ====
195 +
196 +**Data Ingestion:**
197 +
198 +* **Harmonized datasets** stored in **EBRAINS Bucket**.
199 +* **Preprocessing pipelines** clean and standardize data.
200 +
201 +**Feature Engineering:**
202 +
203 +* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
204 +
205 +**AI-Generated Annotations:**
206 +
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 +
122 122  ----
123 123  
124 -== **Final Notes** ==
217 +=== **5. Validation & Real-World Testing** ===
125 125  
126 -Neurodiagnoses continuously expands its data ecosystem to support AI-driven clinical decision-making. Researchers and institutions are encouraged to contribute new datasets and methodologies.
219 +==== **Prospective Clinical Study** ====
127 127  
128 -For additional technical documentation:
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**.
129 129  
130 -* [[GitHub Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
131 -* [[EBRAINS Collaboration Page>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
225 +==== **Quality Assurance & Explainability** ====
132 132  
133 -If you experience issues integrating data, open a [[GitHub Issue>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]] or consult the EBRAINS Neurodiagnoses Forum.
227 +* **Annotations linked to structured knowledge graphs** for improved transparency.
228 +* **Interactive annotation editor** allows clinicians to validate AI outputs.
229 +
230 +----
231 +
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 +
245 +----
246 +
247 +=== **7. Tools and Technologies** ===
248 +
249 +==== **Programming Languages:** ====
250 +
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 +
267 +----
268 +
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.