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1 -**# Neurodiagnoses AI: Multimodal AI for Neurodiagnostic Predictions**
1 +**Neurodiagnoses AI** is an open-source, AI-driven framework designed to enhance the diagnosis and prognosis of central nervous system (CNS) disorders. Building upon the Florey Dementia Index (FDI) methodology, it now encompasses a broader spectrum of neurological conditions. The system integrates multimodal data sources—including EEG, neuroimaging, biomarkers, and genetics—and employs machine learning models to deliver explainable, real-time diagnostic insights. A key feature of this framework is the incorporation of the **Generalized Neuro Biomarker Ontology Categorization (Neuromarker)**, which standardizes biomarker classification across all neurodegenerative diseases, facilitating cross-disease AI training.
2 2  
3 -## **Project Overview**
4 -Neurodiagnoses AI implements AI-driven diagnostic and prognostic models for central nervous system (CNS) disorders, adapting the Florey Dementia Index (FDI) methodology to a broader set of neurological conditions. The approach integrates **multimodal data sources** (EEG, neuroimaging, biomarkers, and genetics) and employs **machine learning models** to provide **explainable, real-time diagnostic insights**.##
3 +**Neuromarker: Generalized Biomarker Ontology**
5 5  
6 -## **How to Use External Databases in Neurodiagnoses**
7 -To enhance diagnostic accuracy, 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.##
5 +Neuromarker extends the Common Alzheimer’s Disease Research Ontology (CADRO) into a comprehensive biomarker categorization framework applicable to all neurodegenerative diseases (NDDs). This ontology enables standardized classification, AI-based feature extraction, and seamless multimodal data integration.
8 8  
9 -### **Potential Data Sources**
10 -Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases. ##
7 +**Core Biomarker Categories**
11 11  
12 -**Reference: List of Potential Databases**
13 -- **ADNI**: Alzheimer's Disease data ([ADNI](https://adni.loni.usc.edu))
14 -- **PPMI**: Parkinson’s Disease Imaging and biospecimens ([PPMI](https://www.ppmi-info.org))
15 -- **GP2**: Whole-genome sequencing for PD ([GP2](https://gp2.org))
16 -- **Enroll-HD**: Huntington’s Disease Clinical and genetic data ([Enroll-HD](https://www.enroll-hd.org))
17 -- **GAAIN**: Multi-source Alzheimer’s data aggregation ([GAAIN](https://gaain.org))
18 -- **UK Biobank**: Population-wide genetic, imaging, and health records ([UK Biobank](https://www.ukbiobank.ac.uk))
19 -- **DPUK**: Dementia and Aging data ([DPUK](https://www.dementiasplatform.uk))
20 -- **PRION Registry**: Prion Diseases clinical and genetic data ([PRION Registry](https://prionregistry.org))
21 -- **DECIPHER**: Rare genetic disorder genomic variants ([DECIPHER](https://decipher.sanger.ac.uk))
9 +Within the Neurodiagnoses AI framework, biomarkers are categorized as follows:
22 22  
23 -### **1. Register for Access**
24 -- Each external database requires **individual registration** and access approval.
25 -- Ensure compliance with **ethical approvals** and **data usage agreements** before integrating datasets into Neurodiagnoses.
26 -- Some repositories may require a **Data Usage Agreement (DUA)** for sensitive medical data.##
11 +|=**Category**|=**Description**
12 +|**Molecular Biomarkers**|Omics-based markers (genomic, transcriptomic, proteomic, metabolomic, lipidomic)
13 +|**Neuroimaging Biomarkers**|Structural (MRI, CT), Functional (fMRI, PET), Molecular Imaging (tau, amyloid, α-synuclein)
14 +|**Fluid Biomarkers**|CSF, plasma, blood-based markers for tau, amyloid, α-synuclein, TDP-43, GFAP, NfL, autoantiboides
15 +|**Neurophysiological Biomarkers**|EEG, MEG, evoked potentials (ERP), sleep-related markers
16 +|**Digital Biomarkers**|Gait analysis, cognitive/speech biomarkers, wearables data, EHR-based markers
17 +|**Clinical Phenotypic Markers**|Standardized clinical scores (MMSE, MoCA, CDR, UPDRS, ALSFRS, UHDRS)
18 +|**Genetic Biomarkers**|Risk alleles (APOE, LRRK2, MAPT, C9orf72, PRNP) and polygenic risk scores
19 +|**Environmental & Lifestyle Factors**|Toxins, infections, diet, microbiome, comorbidities
27 27  
28 -### **2. Download & Prepare Data**
29 -- Download datasets while adhering to database usage policies.
30 -- Ensure files meet **Neurodiagnoses format requirements**:
31 - - **Tabular Data**: `.csv`, `.tsv`
32 - - **Neuroimaging Data**: `.nii`, `.dcm`
33 - - **Genomic Data**: `.fasta`, `.vcf`
34 - - **Clinical Metadata**: `.json`, `.xml`##
21 +**Integrating External Databases into Neurodiagnoses**
35 35  
36 -- **Mandatory Fields for Integration**:
37 - - **Subject ID**: Unique patient identifier
38 - - **Diagnosis**: Standardized disease classification
39 - - **Biomarkers**: CSF, plasma, or imaging biomarkers
40 - - **Genetic Data**: Whole-genome or exome sequencing
41 - - **Neuroimaging Metadata**: MRI/PET acquisition parameters
23 +To enhance diagnostic precision, Neurodiagnoses AI incorporates data from multiple biomedical and neurological research databases. Researchers can integrate external datasets by following these steps:
42 42  
43 -### **3. Upload Data to Neurodiagnoses**
44 -**Option 1: Upload to EBRAINS Bucket**
45 -- Location: **EBRAINS Neurodiagnoses Bucket**
46 -- Ensure correct **metadata tagging** before submission.##
25 +1. (((
26 +**Register for Access**
47 47  
48 - **Option 2: Contribute via GitHub Repository**
49 -- Location: **GitHub Data Repository**
50 -- Create a new folder under `/data/` and include a **dataset description**.
51 -- For large datasets, contact project administrators before uploading.
28 +* Each external database requires individual registration and access approval.
29 +* Ensure compliance with ethical approvals and data usage agreements before integrating datasets into Neurodiagnoses.
30 +* Some repositories may require a Data Usage Agreement (DUA) for sensitive medical data.
31 +)))
32 +1. (((
33 +**Download & Prepare Data**
52 52  
53 -### **4. Integrate Data into AI Models**
54 -- Open **Jupyter Notebooks** on EBRAINS to run **preprocessing scripts**.
55 -- Standardize **neuroimaging and biomarker formats** using harmonization tools.
56 -- Use **machine learning models** to handle missing data and feature extraction.
57 -- Train AI models with **newly integrated patient cohorts**.##
35 +* Download datasets while adhering to database usage policies.
36 +* (((
37 +Ensure files meet Neurodiagnoses format requirements:
58 58  
59 -**Reference**: See `docs/data_processing.md` for detailed instructions.
39 +|=**Data Type**|=**Accepted Formats**
40 +|**Tabular Data**|.csv, .tsv
41 +|**Neuroimaging**|.nii, .dcm
42 +|**Genomic Data**|.fasta, .vcf
43 +|**Clinical Metadata**|.json, .xml
44 +)))
45 +* (((
46 +**Mandatory Fields for Integration**:
60 60  
61 -## **Collaboration & Partnerships**##
62 -# **Partnering with Data Providers**
63 -Neurodiagnoses seeks partnerships with data repositories to:
64 -- Enable **API-based data integration** for real-time processing.
65 -- Co-develop **harmonized AI-ready datasets** with standardized annotations.
66 -- Secure **funding opportunities** through joint grant applications.
48 +* Subject ID: Unique patient identifier
49 +* Diagnosis: Standardized disease classification
50 +* Biomarkers: CSF, plasma, or imaging biomarkers
51 +* Genetic Data: Whole-genome or exome sequencing
52 +* Neuroimaging Metadata: MRI/PET acquisition parameters
53 +)))
54 +)))
55 +1. (((
56 +**Upload Data to Neurodiagnoses**
67 67  
68 -**Interested in Partnering?**
69 -- If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
70 -- **Contact**: info@neurodiagnoses.com
71 -
72 -## **Final Notes**
73 -Neurodiagnoses continuously expands its data ecosystem to support AI-driven clinical decision-making. Researchers and institutions are encouraged to contribute **new datasets and methodologies**.##
74 -
75 -For additional technical documentation:
76 -- **GitHub Repository**: [Neurodiagnoses GitHub](https://github.com/neurodiagnoses)
77 -- **EBRAINS Collaboration Page**: [EBRAINS Neurodiagnoses](https://ebrains.eu/collabs/neurodiagnoses)
78 -
79 -If you experience issues integrating data, **open a GitHub Issue** or consult the **EBRAINS Neurodiagnoses Forum**.
80 -
81 -== **How to Use External Databases in Neurodiagnoses** ==
82 -
83 -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.
84 -
85 -=== **Potential Data Sources** ===
86 -
87 -Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
88 -
89 -* Reference: [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
90 -
91 -=== **1. Register for Access** ===
92 -
93 -Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
94 -
95 -* Ensure that you have completed all ethical approvals and data access agreements before integrating datasets into Neurodiagnoses.
96 -* Some repositories require a Data Usage Agreement (DUA) before downloading sensitive medical data.
97 -
98 -=== **2. Download & Prepare Data** ===
99 -
100 -Once access is granted, download datasets while complying with data usage policies. Ensure that the files meet Neurodiagnoses’ format requirements for smooth integration.
101 -
102 -==== **Supported File Formats** ====
103 -
104 -* Tabular Data: .csv, .tsv
105 -* Neuroimaging Data: .nii, .dcm
106 -* Genomic Data: .fasta, .vcf
107 -* Clinical Metadata: .json, .xml
108 -
109 -==== **Mandatory Fields for Integration** ====
110 -
111 -|=Field Name|=Description
112 -|Subject ID|Unique patient identifier
113 -|Diagnosis|Standardized disease classification
114 -|Biomarkers|CSF, plasma, or imaging biomarkers
115 -|Genetic Data|Whole-genome or exome sequencing
116 -|Neuroimaging Metadata|MRI/PET acquisition parameters
117 -
118 -=== **3. Upload Data to Neurodiagnoses** ===
119 -
120 -Once preprocessed, data can be uploaded to EBRAINS or GitHub.
121 -
122 122  * (((
123 123  **Option 1: Upload to EBRAINS Bucket**
124 124  
125 -* Location: [[EBRAINS Neurodiagnoses Bucket>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
61 +* Location: EBRAINS Neurodiagnoses Bucket
126 126  * Ensure correct metadata tagging before submission.
127 127  )))
128 128  * (((
129 129  **Option 2: Contribute via GitHub Repository**
130 130  
131 -* Location: [[GitHub Data Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/tree/main/data]]
132 -* Create a new folder under /data/ and include dataset description.
67 +* Location: GitHub Data Repository
68 +* Create a new folder under /data/ and include a dataset description.
69 +* For large datasets, contact project administrators before uploading.
133 133  )))
71 +)))
72 +1. (((
73 +**Integrate Data into AI Models**
134 134  
135 -//Note: For large datasets, please contact the project administrators before uploading.//
136 -
137 -=== **4. Integrate Data into AI Models** ===
138 -
139 -Once uploaded, datasets must be harmonized and formatted before AI model training.
140 -
141 -==== **Steps for Data Integration** ====
142 -
143 143  * Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
144 144  * Standardize neuroimaging and biomarker formats using harmonization tools.
145 -* Use machine learning models to handle missing data and feature extraction.
77 +* Utilize machine learning models to handle missing data and feature extraction.
146 146  * Train AI models with newly integrated patient cohorts.
147 -* 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]].
148 148  
149 -----
80 +**Reference**: See docs/data_processing.md for detailed instructions.
81 +)))
150 150  
151 -== **Database Sources Table** ==
83 +**AI-Driven Biomarker Categorization**
152 152  
153 -=== **Where to Insert This** ===
85 +Neurodiagnoses employs advanced AI models for biomarker classification:
154 154  
155 -* GitHub: [[docs/data_sources.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/data_sources.md]]
156 -* EBRAINS Wiki: Collabs/neurodiagnoses/Data Sources
87 +|=**Model Type**|=**Application**
88 +|**Graph Neural Networks (GNNs)**|Identify shared biomarker pathways across diseases
89 +|**Contrastive Learning**|Distinguish overlapping vs. unique biomarkers
90 +|**Multimodal Transformer Models**|Integrate imaging, omics, and clinical data
157 157  
158 -=== **Key Databases for Neurodiagnoses** ===
92 +**Collaboration & Partnerships**
159 159  
160 -|=Database|=Focus Area|=Data Type|=Access Link
161 -|ADNI|Alzheimer's Disease|MRI, PET, CSF, cognitive tests|ADNI
162 -|PPMI|Parkinson’s Disease|Imaging, biospecimens|[[PPMI>>url:https://www.ppmi-info.org/]]
163 -|GP2|Genetic Data for PD|Whole-genome sequencing|[[GP2>>url:https://gp2.org/]]
164 -|Enroll-HD|Huntington’s Disease|Clinical, genetic, imaging|[[Enroll-HD>>url:https://enroll-hd.org/]]
165 -|GAAIN|Alzheimer's & Cognitive Decline|Multi-source data aggregation|[[GAAIN>>url:https://www.gaain.org/]]
166 -|UK Biobank|Population-wide studies|Genetic, imaging, health records|[[UK Biobank>>url:https://www.ukbiobank.ac.uk/]]
167 -|DPUK|Dementia & Aging|Imaging, genetics, lifestyle factors|[[DPUK>>url:https://www.dementiasplatform.uk/]]
168 -|PRION Registry|Prion Diseases|Clinical and genetic data|[[PRION Registry>>url:https://www.prionalliance.org/]]
169 -|DECIPHER|Rare Genetic Disorders|Genomic variants|DECIPHER
94 +Neurodiagnoses actively seeks partnerships with data providers to:
170 170  
171 -If you know a relevant dataset, submit a proposal in [[GitHub Issues>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]].
172 -
173 -----
174 -
175 -== **Collaboration & Partnerships** ==
176 -
177 -=== **Where to Insert This** ===
178 -
179 -* GitHub: [[docs/collaboration.md>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/docs/collaboration.md]]
180 -* EBRAINS Wiki: Collabs/neurodiagnoses/Collaborations
181 -
182 -=== **Partnering with Data Providers** ===
183 -
184 -Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
185 -
186 -* Enable direct API-based data integration for real-time processing.
96 +* Enable API-based data integration for real-time processing.
187 187  * Co-develop harmonized AI-ready datasets with standardized annotations.
188 188  * Secure funding opportunities through joint grant applications.
189 189  
190 -=== **Interested in Partnering?** ===
100 +**Interested in Partnering?**
191 191  
192 192  If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
193 193  
194 -* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
104 +**Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
195 195  
196 -----
197 -
198 -== **Final Notes** ==
199 -
200 -Neurodiagnoses continuously expands its data ecosystem to support AI-driven clinical decision-making. Researchers and institutions are encouraged to contribute new datasets and methodologies.
201 -
202 -For additional technical documentation:
203 -
204 -* [[GitHub Repository>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses]]
205 -* [[EBRAINS Collaboration Page>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/]]
206 -
207 -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.
106 +
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