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1		-Here is the updated **Methodology** section for the EBRAINS Wiki, incorporating the **Generalized Neuro Biomarker Ontology Categorization (Neuromarker)** for **biomarker classification across all neurodegenerative diseases**.
	1	+**Neurodiagnoses AI** is an open-source, AI-driven framework designed to enhance the diagnosis and prognosis of central nervous system (CNS) disorders. It 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) **and** Disease Knowledge Transfer (DKT)**, which standardizes disease and biomarker classification across all CNS diseases, facilitating cross-disease AI training.
2	2
3		-----
	3	+**Neuromarker: Generalized Biomarker Ontology**
4	4
5		-== **Neurodiagnoses AI: Multimodal AI for Neurodiagnostic Predictions** ==
	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.
6	6
7		-=== **Project Overview** ===
	7	+**Recommended Software**
8	8
9		-Neurodiagnoses AI implements **AI-driven diagnostic and prognostic models** for central nervous system (CNS) disorders, expanding 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**. This framework now incorporates **Neuromarker**, a **generalized biomarker ontology** that categorizes biomarkers across neurodegenerative diseases, enabling **standardized, cross-disease AI training**.
	9	+There is a suite of software that can help implement the workflow needed in Neurodiagnoses. Find a list of recommendations [[here>>https://github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/recommended_software]].
10	10
11		-== **Neuromarker: Generalized Biomarker Ontology** ==
	11	+**Core Biomarker Categories**
12	12
13		-Neuromarker extends the **Common Alzheimer’s Disease Research Ontology (CADRO)** into a **cross-disease biomarker categorization framework** applicable to all neurodegenerative diseases (NDDs). It allows for **standardized classification, AI-based feature extraction, and multimodal integration**.
	13	+Within the Neurodiagnoses AI framework, biomarkers are categorized as follows:
14	14
15		-=== **Core Biomarker Categories** ===
16		-
17		-The following ontology is used within **Neurodiagnoses AI** for biomarker categorization:
18		-
19	19	|=**Category**|=**Description**
20	20	|**Molecular Biomarkers**|Omics-based markers (genomic, transcriptomic, proteomic, metabolomic, lipidomic)
21	21	|**Neuroimaging Biomarkers**|Structural (MRI, CT), Functional (fMRI, PET), Molecular Imaging (tau, amyloid, α-synuclein)
22		-|**Fluid Biomarkers**|CSF, plasma, blood-based markers for tau, amyloid, α-synuclein, TDP-43, GFAP, NfL
	18	+|**Fluid Biomarkers**|CSF, plasma, blood-based markers for tau, amyloid, α-synuclein, TDP-43, GFAP, NfL, autoantiboides
23	23	|**Neurophysiological Biomarkers**|EEG, MEG, evoked potentials (ERP), sleep-related markers
24	24	|**Digital Biomarkers**|Gait analysis, cognitive/speech biomarkers, wearables data, EHR-based markers
25	25	|**Clinical Phenotypic Markers**|Standardized clinical scores (MMSE, MoCA, CDR, UPDRS, ALSFRS, UHDRS)
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26	26	|**Genetic Biomarkers**|Risk alleles (APOE, LRRK2, MAPT, C9orf72, PRNP) and polygenic risk scores
27	27	|**Environmental & Lifestyle Factors**|Toxins, infections, diet, microbiome, comorbidities
28	28
29		-----
	25	+**Integrating External Databases into Neurodiagnoses**
30	30
31		-== **How to Use External Databases in Neurodiagnoses** ==
	27	+To enhance diagnostic precision, Neurodiagnoses AI incorporates data from multiple biomedical and neurological research databases. Researchers can integrate external datasets by following these steps:
32	32
33		-To enhance diagnostic accuracy, Neurodiagnoses AI integrates data from **multiple biomedical and neurological research databases**. Researchers can follow these steps to access, prepare, and integrate data into the Neurodiagnoses framework.
	29	+1. (((
	30	+**Register for Access**
34	34
35		-=== **Potential Data Sources** ===
	32	+* Each external database requires individual registration and access approval.
	33	+* Ensure compliance with ethical approvals and data usage agreements before integrating datasets into Neurodiagnoses.
	34	+* Some repositories may require a Data Usage Agreement (DUA) for sensitive medical data.
	35	+)))
	36	+1. (((
	37	+**Download & Prepare Data**
36	36
37		-Neurodiagnoses maintains an **updated list** of biomedical datasets relevant to neurodegenerative diseases:
	39	+* Download datasets while adhering to database usage policies.
	40	+* (((
	41	+Ensure files meet Neurodiagnoses format requirements:
38	38
39		-* **ADNI**: Alzheimer's Disease Imaging & Biomarkers → [[ADNI>>url:https://adni.loni.usc.edu/]]
40		-* **PPMI**: Parkinson’s Disease Imaging & Biospecimens → [[PPMI>>url:https://www.ppmi-info.org/]]
41		-* **GP2**: Whole-Genome Sequencing for PD → [[GP2>>url:https://gp2.org/]]
42		-* **Enroll-HD**: Huntington’s Disease Clinical & Genetic Data → [[Enroll-HD>>url:https://www.enroll-hd.org/]]
43		-* **GAAIN**: Multi-Source Alzheimer’s Data Aggregation → [[GAAIN>>url:https://gaain.org/]]
44		-* **UK Biobank**: Population-Wide Genetic, Imaging & Health Records → [[UK Biobank>>url:https://www.ukbiobank.ac.uk/]]
45		-* **DPUK**: Dementia & Aging Data → [[DPUK>>url:https://www.dementiasplatform.uk/]]
46		-* **PRION Registry**: Prion Diseases Clinical & Genetic Data → [[PRION Registry>>url:https://prionregistry.org/]]
47		-* **DECIPHER**: Rare Genetic Disorder Genomic Variants → [[DECIPHER>>url:https://decipher.sanger.ac.uk/]]
48		-
49		-----
50		-
51		-== **1. Register for Access** ==
52		-
53		-* Each external database requires **individual registration and access approval**.
54		-* Ensure compliance with **ethical approvals and data usage agreements** before integrating datasets into Neurodiagnoses.
55		-* Some repositories may require a **Data Usage Agreement (DUA)** for sensitive medical data.
56		-
57		-----
58		-
59		-== **2. Download & Prepare Data** ==
60		-
61		-* Download datasets while adhering to **database usage policies**.
62		-* Ensure files meet **Neurodiagnoses format requirements**:
63		-
64	64	|=**Data Type**|=**Accepted Formats**
65	65	|**Tabular Data**|.csv, .tsv
66	66	|**Neuroimaging**|.nii, .dcm
67	67	|**Genomic Data**|.fasta, .vcf
68	68	|**Clinical Metadata**|.json, .xml
	48	+)))
	49	+* (((
	50	+**Mandatory Fields for Integration**:
69	69
70		-* **Mandatory Fields for Integration**:
71		-** **Subject ID**: Unique patient identifier
72		-** **Diagnosis**: Standardized disease classification
73		-** **Biomarkers**: CSF, plasma, or imaging biomarkers
74		-** **Genetic Data**: Whole-genome or exome sequencing
75		-** **Neuroimaging Metadata**: MRI/PET acquisition parameters
	52	+* Subject ID: Unique patient identifier
	53	+* Diagnosis: Standardized disease classification
	54	+* Biomarkers: CSF, plasma, or imaging biomarkers
	55	+* Genetic Data: Whole-genome or exome sequencing
	56	+* Neuroimaging Metadata: MRI/PET acquisition parameters
	57	+)))
	58	+)))
	59	+1. (((
	60	+**Upload Data to Neurodiagnoses**
76	76
77		-----
	62	+* (((
	63	+**Option 1: Upload to EBRAINS Bucket**
78	78
79		-== **3. Upload Data to Neurodiagnoses** ==
	65	+* Location: EBRAINS Neurodiagnoses Bucket
	66	+* Ensure correct metadata tagging before submission.
	67	+)))
	68	+* (((
	69	+**Option 2: Contribute via GitHub Repository**
80	80
81		-=== **Option 1: Upload to EBRAINS Bucket** ===
	71	+* Location: GitHub Data Repository
	72	+* Create a new folder under /data/ and include a dataset description.
	73	+* For large datasets, contact project administrators before uploading.
	74	+)))
	75	+)))
	76	+1. (((
	77	+**Integrate Data into AI Models**
82	82
83		-* Location: **EBRAINS Neurodiagnoses Bucket**
84		-* Ensure **correct metadata tagging** before submission.
	79	+* Open Jupyter Notebooks on EBRAINS to run preprocessing scripts.
	80	+* Standardize neuroimaging and biomarker formats using harmonization tools.
	81	+* Utilize machine learning models to handle missing data and feature extraction.
	82	+* Train AI models with newly integrated patient cohorts.
85	85
86		-=== **Option 2: Contribute via GitHub Repository** ===
87		-
88		-* Location: **GitHub Data Repository**
89		-* Create a **new folder under /data/** and include a **dataset description**.
90		-* **For large datasets**, contact project administrators before uploading.
91		-
92		-----
93		-
94		-== **4. Integrate Data into AI Models** ==
95		-
96		-* Open **Jupyter Notebooks** on EBRAINS to run **preprocessing scripts**.
97		-* **Standardize neuroimaging and biomarker formats** using harmonization tools.
98		-* Use **machine learning models** to handle **missing data** and **feature extraction**.
99		-* Train AI models with **newly integrated patient cohorts**.
100		-
101	101	**Reference**: See docs/data_processing.md for detailed instructions.
	85	+)))
102	102
103		-----
	87	+**AI-Driven Biomarker Categorization**
104	104
105		-== **AI-Driven Biomarker Categorization** ==
	89	+Neurodiagnoses employs advanced AI models for biomarker classification:
106	106
107		-Neurodiagnoses employs **AI models** for biomarker classification:
108		-
109	109	|=**Model Type**|=**Application**
110	110	|**Graph Neural Networks (GNNs)**|Identify shared biomarker pathways across diseases
111	111	|**Contrastive Learning**|Distinguish overlapping vs. unique biomarkers
112	112	|**Multimodal Transformer Models**|Integrate imaging, omics, and clinical data
113	113
114		-----
	96	+**Collaboration & Partnerships**
115	115
116		-== **Collaboration & Partnerships** ==
	98	+Neurodiagnoses actively seeks partnerships with data providers to:
117	117
118		-=== **Partnering with Data Providers** ===
	100	+* Enable API-based data integration for real-time processing.
	101	+* Co-develop harmonized AI-ready datasets with standardized annotations.
	102	+* Secure funding opportunities through joint grant applications.
119	119
120		-Neurodiagnoses seeks partnerships with data repositories to:
121		-
122		-* Enable **API-based data integration** for real-time processing.
123		-* Co-develop **harmonized AI-ready datasets** with standardized annotations.
124		-* Secure **funding opportunities** through joint grant applications.
125		-
126	126	**Interested in Partnering?**
127	127
128		-* If you represent a **research consortium or database provider**, reach out to explore **data-sharing agreements**.
129		-* **Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
	106	+If you represent a research consortium or database provider, reach out to explore data-sharing agreements.
130	130
131		-----
	108	+**Contact**: [[info@neurodiagnoses.com>>mailto:info@neurodiagnoses.com]]
132	132
133		-== **Final Notes** ==
	110	+**Final Notes**
134	134
135		-Neurodiagnoses continuously expands its **data ecosystem** to support **AI-driven clinical decision-making**. Researchers and institutions are encouraged to **contribute new datasets and methodologies**.
	112	+Neurodiagnoses AI is committed to advancing the integration of artificial intelligence in neurodiagnostic processes. By continuously expanding our data ecosystem and incorporating standardized biomarker classifications through the Neuromarker ontology, we aim to enhance cross-disease AI training and improve diagnostic accuracy across neurodegenerative disorders.
136	136
137		-**For additional technical documentation**:
	114	+We encourage researchers and institutions to contribute new datasets and methodologies to further enrich this collaborative platform. Your participation is vital in driving innovation and fostering a deeper understanding of complex neurological conditions.
138	138
139		-* **GitHub Repository**: [[Neurodiagnoses GitHub>>url:https://github.com/neurodiagnoses]]
140		-* **EBRAINS Collaboration Page**: [[EBRAINS Neurodiagnoses>>url:https://ebrains.eu/collabs/neurodiagnoses]]
	116	+**For additional technical documentation and collaboration opportunities:**
141	141
142		-**If you experience issues integrating data**, open a **GitHub Issue** or consult the **EBRAINS Neurodiagnoses Forum**.
	118	+* **GitHub Repository:** [[Neurodiagnoses GitHub>>url:https://github.com/neurodiagnoses]]
	119	+* **EBRAINS Collaboration Page:** [[EBRAINS Neurodiagnoses>>url:https://ebrains.eu/collabs/neurodiagnoses]]
143	143
144		-----
145		-
146		-This **updated methodology** now incorporates [[https:~~/~~/github.com/Fundacion-de-Neurociencias/neurodiagnoses/blob/main/data/biomarker_ontology>>https://Neuromarker]] for standardized biomarker classification, enabling **cross-disease AI training** across neurodegenerative disorders.
	121	+If you encounter any issues during data integration or have suggestions for improvement, please open a GitHub Issue or consult the EBRAINS Neurodiagnoses Forum. Together, we can advance the field of neurodiagnostics and contribute to better patient outcomes.

workflow neurodiagnoses.png

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