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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.
	1	+== **Overview** ==
2	2
3		-**Neuromarker: Generalized Biomarker Ontology**
	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.
4	4
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.
	5	+----
6	6
7		-**Core Biomarker Categories**
	7	+== **How to Use External Databases in Neurodiagnoses** ==
8	8
9		-Within the Neurodiagnoses AI framework, biomarkers are categorized as follows:
	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.
10	10
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
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
	11	+=== **Potential Data Sources** ===
20	20
21		-**Integrating External Databases into Neurodiagnoses**
	13	+Neurodiagnoses maintains an updated list of potential biomedical databases relevant to neurodegenerative diseases.
22	22
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:
	15	+* Reference: [[List of Potential Databases>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/sources/list_of_potential_databases]]
24	24
25		-1. (((
26		-**Register for Access**
	17	+=== **1. Register for Access** ===
27	27
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**
	19	+Each external database requires individual registration and access approval. Follow the official guidelines of each database provider.
34	34
35		-* Download datasets while adhering to database usage policies.
36		-* (((
37		-Ensure files meet Neurodiagnoses format requirements:
	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.
38	38
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**:
	24	+=== **2. Download & Prepare Data** ===
47	47
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**
	26	+Once access is granted, download datasets while complying with data usage policies. Ensure that the files meet Neurodiagnoses’ format requirements for smooth integration.
57	57
	28	+==== **Supported File Formats** ====
	29	+
	30	+* Tabular Data: .csv, .tsv
	31	+* Neuroimaging Data: .nii, .dcm
	32	+* Genomic Data: .fasta, .vcf
	33	+* Clinical Metadata: .json, .xml
	34	+
	35	+==== **Mandatory Fields for Integration** ====
	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
	43	+
	44	+=== **3. Upload Data to Neurodiagnoses** ===
	45	+
	46	+Once preprocessed, data can be uploaded to EBRAINS or GitHub.
	47	+
58	58	* (((
59	59	**Option 1: Upload to EBRAINS Bucket**
60	60
61		-* Location: EBRAINS Neurodiagnoses Bucket
	51	+* Location: [[EBRAINS Neurodiagnoses Bucket>>url:https://wiki.ebrains.eu/bin/view/Collabs/neurodiagnoses/Bucket]]
62	62	* Ensure correct metadata tagging before submission.
63	63	)))
64	64	* (((
65	65	**Option 2: Contribute via GitHub Repository**
66	66
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.
	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.
70	70	)))
71		-)))
72		-1. (((
73		-**Integrate Data into AI Models**
74	74
	61	+//Note: For large datasets, please contact the project administrators before uploading.//
	62	+
	63	+=== **4. Integrate Data into AI Models** ===
	64	+
	65	+Once uploaded, datasets must be harmonized and formatted before AI model training.
	66	+
	67	+==== **Steps for Data Integration** ====
	68	+
75	75	* Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
76	76	* Standardize neuroimaging and biomarker formats using harmonization tools.
77		-* Utilize machine learning models to handle missing data and feature extraction.
	71	+* Use machine learning models to handle missing data and feature extraction.
78	78	* 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]].
79	79
80		-**Reference**: See docs/data_processing.md for detailed instructions.
81		-)))
	75	+----
82	82
83		-**AI-Driven Biomarker Categorization**
	77	+== **Database Sources Table** ==
84	84
85		-Neurodiagnoses employs advanced AI models for biomarker classification:
	79	+=== **Where to Insert This** ===
86	86
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
	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
91	91
92		-**Collaboration & Partnerships**
	84	+=== **Key Databases for Neurodiagnoses** ===
93	93
94		-Neurodiagnoses actively seeks partnerships with data providers to:
	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
95	95
96		-* Enable API-based data integration for real-time processing.
	97	+If you know a relevant dataset, submit a proposal in [[GitHub Issues>>url:https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/issues]].
	98	+
	99	+----
	100	+
	101	+== **Collaboration & Partnerships** ==
	102	+
	103	+=== **Where to Insert This** ===
	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
	107	+
	108	+=== **Partnering with Data Providers** ===
	109	+
	110	+Beyond using existing datasets, Neurodiagnoses seeks partnerships with data repositories to:
	111	+
	112	+* Enable direct API-based data integration for real-time processing.
97	97	* Co-develop harmonized AI-ready datasets with standardized annotations.
98	98	* Secure funding opportunities through joint grant applications.
99	99
100		-**Interested in Partnering?**
	116	+=== **Interested in Partnering?** ===
101	101
102	102	If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
103	103
104		-**Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
	120	+* Contact: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
105	105
106		-
	122	+----
	123	+
	124	+== **Final Notes** ==
	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.
	127	+
	128	+For additional technical documentation:
	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/]]
	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.

workflow neurodiagnoses.png

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