Editing AIDAVA Competitive Analysis (section)

== Market Map: Who Does What ==

Health data curation is a pipeline with multiple steps. No single existing commercial product covers the full pipeline from raw heterogeneous data to published, interoperable, reuse-ready health records.

{| class="wikitable"
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! Pipeline Step !! What It Means !! Who Does It !! AIDAVA?
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| '''1. Data Collection''' || Gathering raw records from hospitals, labs, EHRs || [[PicnicHealth]] (US, patient-anchored), [[1upHealth]] (FHIR-based), [[TriNetX]] (site-based network) || Yes — ingests structured + unstructured data
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| '''2. Data Standards''' || Structuring data using FHIR, HL7, openEHR || [[Better]] (FHIR platform), [[InterSystems]] (HealthShare), [[Lifen]] (document exchange) || Yes — FHIR resource profiles as structural framework
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| '''3. NLP / Text Extraction''' || Extracting structured data from clinical narratives, discharge notes, reports || [[Cogstack]] (NHS NLP), [[Qantev]] (claims NLP), [[Averbis]] (German NLP) || Yes — deep learning for 3 languages
|-
| '''4. Knowledge Graphs''' || Representing clinical data as semantic graphs with ontology relationships || [[Healx]] (drug repurposing KGs), [[Ada Health]] (medical knowledge base) || Yes — PHKG based on SNOMED/LOINC/FHIR ontologies
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| '''5. FAIRification''' || Making data Findable, Accessible, Interoperable, Reusable || [[Castor EDC]] (trial data FAIRification), academic projects (Swiss PHN) || Yes — automated FAIRification pillar
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| '''6. Patient Interaction''' || Patients see, understand, and approve curation decisions || [[PicnicHealth]] (record access), [[Loovi]] (biomarker results) || Yes — explainable AI adapted to user knowledge level
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| '''7. Multi-stakeholder Reuse''' || Same curated data serves patients, clinicians, AND researchers || '''No existing commercial product does this''' || Yes — "curate once, reuse many times"
|}