Summary

• Page properties (1 modified, 0 added, 0 removed)

Details

Page properties

Content

...	...	@@ -1,268 +1,154 @@
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.
97		-
98		-For further information, refer to **[[Clinica.Run Documentation>>url:https://clinica.run/]]**.
99		-
100		-==== ====
101		-
102		-==== **Data Sources** ====
103		-
104		-[[List of potential sources of databases>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
105		-
106		-**Biomedical Ontologies & Databases:**
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** ====
	84	+== **Clinical Decision Support & Tridimensional Diagnostic Framework** ==
133	133
134		-To ensure **structured integration of diverse datasets**, **Neurodiagnoses** will implement an **AI-driven annotation system**, which will:
	86	+Neurodiagnoses generates **structured AI reports** for clinicians, combining:
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.
	88	+**Probabilistic Diagnosis:** AI-generated ranking of potential diagnoses.
	89	+**Tridimensional Classification:** Standardized diagnostic reports based on:
139	139
140		-----
	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.
141	141
142		-== **2. AI-Based Analysis** ==
	95	+**Reference:** [[Tridimensional Classification Guide>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/classification.md]]
143	143
144		-==== **Machine Learning & Deep Learning Models** ====
145		-
146		-**Risk Prediction Models:**
147		-
148		-* **LETHE’s cognitive risk prediction model** integrated into the annotation framework.
149		-
150		-**Biomarker Classification & Probabilistic Imputation:**
151		-
152		-* **KNN Imputer** and **Bayesian models** used for handling **missing biomarker data**.
153		-
154		-**Neuroimaging Feature Extraction:**
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** ==
	99	+== **Data Security, Compliance & Federated Learning** ==
167	167
168		-==== **Tridimensional Diagnostic Axes** ====
	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.
169	169
170		-**Axis 1: Etiology (Pathogenic Mechanisms)**
	105	+**Reference:** [[Data Protection & Federated Learning>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/security.md]]
171	171
172		-* Classification based on **genetic markers, cellular pathways, and environmental risk factors**.
173		-* **AI-assisted annotation** provides **causal interpretations** for clinical use.
174		-
175		-**Axis 2: Molecular Markers & Biomarkers**
176		-
177		-* **Integration of CSF, blood, and neuroimaging biomarkers**.
178		-* **Structured annotation** highlights **biological pathways linked to diagnosis**.
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** ==
	109	+== **Data Processing & Integration with Clinica.Run** ==
188	188
189		-==== **Data Processing Steps** ====
	111	+Neurodiagnoses now supports **Clinica.Run**, an **open-source neuroimaging platform** for **multimodal data processing.**
190	190
191		-**Data Ingestion:**
	113	+=== **How It Works** ===
192	192
193		-* **Harmonized datasets** stored in **EBRAINS Bucket**.
194		-* **Preprocessing pipelines** clean and standardize data.
	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.**
195	195
196		-**Feature Engineering:**
	119	+=== **Implementation Steps** ===
197	197
198		-* **AI models** extract **clinically relevant patterns** from **EEG, MRI, and biomarkers**.
	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.
199	199
200		-**AI-Generated Annotations:**
	125	+**Reference:** [[Clinica.Run Documentation>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/clinica_run.md]]
201	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** ==
	129	+== **Collaborative Development & Research** ==
213	213
214		-==== **Prospective Clinical Study** ====
	131	+**We Use GitHub to Develop AI Models & Store Research Data**
215	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**.
	133	+* **GitHub Repository:** AI model training scripts.
	134	+* **GitHub Issues:** Tracks ongoing research questions.
	135	+* **GitHub Wiki:** Project documentation & user guides.
219	219
220		-==== **Quality Assurance & Explainability** ====
	137	+**We Use EBRAINS for Data & Collaboration**
221	221
222		-* **Annotations linked to structured knowledge graphs** for improved transparency.
223		-* **Interactive annotation editor** allows clinicians to validate AI outputs.
	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.
224	224
225		-----
	143	+**Join the Project Forum:** [[GitHub Discussions>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/discussions]]
226	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	240	----
241	241
242		-== **7. Tools and Technologies** ==
	147	+**For Additional Documentation:**
243	243
244		-==== **Programming Languages:** ====
	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/]]
245	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.
261		-
262	262	----
263	263
264		-=== **Why This Matters** ===
265		-
266		-* The annotation system ensures that AI-generated insights are structured, interpretable, and clinically meaningful.
267		-* It enables real-time tracking of disease progression across the three diagnostic axes.
268		-* It facilitates integration with electronic health records and decision-support tools, improving AI adoption in clinical workflows.
	154	+**Neurodiagnoses is Open for Contributions – Join Us Today!**