APPRE: A Schema-and-Rules Framework for Adaptive Measurement, Confounder Annotation, and Response-Policy Documentation in Complex Neurovascular Disease
Abstract
This Zenodo record archives Paper 4 of the RAY-VASC Regenerative Loop research sequence. Paper 4 introduces APPRE as a schema-and-rules framework for adaptive measurement, confounder annotation, adverse-event capture, missingness handling, provenance, synthetic-data release, and response-policy documentation in RAY-VASC-style N-of-1 and small-series complex neurovascular research. APPRE is not validated artificial intelligence, not clinical decision support, not Software as a Medical Device, not a treatment optimizer, and not a longevity product. No clinical outcomes are reported in this manuscript. The figure-integrated v1.0.0 release includes the public manuscript and a release bundle containing architecture figures, schema/data supplements, synthetic-data materials, validation-rule documentation, release metadata, and governance files. Controlled-substance exposure, if present in future lawful research implementations, is documented only as as-administered observational data under separate lawful, clinician-governed, ethics-approved oversight. APPRE does not recommend, adjust, tune, or optimize controlled-substance exposure. Not medical advice. Not legal advice.
Fields of Study & Subjects
Functional Brain Connectivity Studies
Statistical Methods in Clinical Trials
Machine Learning in Healthcare
Publication details
- Journal / source
- OSF Preprints (OSF Preprints)
- Publication date
- 2 July 2026
- Language
- EN
- Document type
- Preprint