Maziyar Panahi

Runs a HIPAA Privacy and Security Rule checklist over a data pipeline and produces a gap report before deploying OpenMed on PHI. Use when the user is about to process protected health information, needs a pre-deployment compliance review, wants to know which administrative, physical, and technical safeguards apply, is scoping a Business Associate Agreement, or must document minimum-necessary and de-identification controls. Trigger keywords: HIPAA, Privacy Rule, Security Rule, 45 CFR 164, PHI, BAA, business associate, minimum necessary, safeguards, Safe Harbor, Expert Determination, gap analysi

Security · maziyarpanahi/openmed

Suggests candidate ICD-10-CM diagnosis codes (and ICD-10-PCS procedure codes) for diagnoses and procedures extracted by OpenMed, with rationale and a human-coder caveat. Use when the user wants to code a problem list, map a diagnosis span to a billable ICD-10-CM code, route a finding to the right chapter, cross-walk ICD-9 via GEMs, or pre-fill an encounter for coder review. Trigger keywords: ICD-10-CM, ICD-10-PCS, diagnosis coding, billable code, GEMs, problem list coding, encounter diagnosis, chapter range, CMS code lookup. references/icd10-chapters.md holds the chapter/section ranges. Pairs

Code Review & Quality · maziyarpanahi/openmed

Map OpenMed-extracted, terminology-coded conditions, drugs, and measurements into OMOP CDM v5.4 clinical tables (condition_occurrence, drug_exposure, measurement) for OHDSI/ATLAS analytics. Use when the user wants to load NLP-derived facts into an OMOP database, build an OHDSI ETL from clinical notes, populate condition_occurrence or drug_exposure from text, or standardize note-derived findings to OMOP standard concepts. Covers the source-to-standard concept mapping pattern, required vs optional CDM fields, type concepts for NLP-derived rows, and the user-supplied OHDSI vocabulary (CONCEPT/CON

Databases · maziyarpanahi/openmed

Verify OpenMed de-identified output against all 18 HIPAA Safe Harbor identifier categories and report residual re-identification risk. Use when the user must confirm a note meets HIPAA Safe Harbor (45 CFR 164.514(b)(2)), needs a coverage checklist mapping detected entities to the 18 categories, wants to flag gaps like ages over 89, rare geography, fax vs phone, or biometrics, or asks whether masking was complete. Maps OpenMed CANONICAL_LABELS to the 18 HIPAA classes and uses extract_pii / deidentify to check coverage. Pairs with OpenMed deidentifying-clinical-text and auditing-deidentification

Testing & QA · maziyarpanahi/openmed

Turn scanned faxes, images, and CSV/CDA exports into clean text ready for OpenMed de-identification and NER, fully on-device. Use when the user has clinical documents (image scans, photographed/faxed notes, tabular CSV/TSV exports, C-CDA XML) and needs OCR or structured intake before openmed.deidentify and openmed.analyze_text, asks about openmed.multimodal, OCR engines (Tesseract / PaddleOCR), tabular redaction, or layout and reading order. Covers the verified ocr() and redact_document() entry points and the ExtractedDocument contract. Pairs before deidentifying-clinical-text and extracting-c

Data & Analytics · maziyarpanahi/openmed

Extracts social determinants of health (SDOH) — housing instability, food insecurity, unemployment, transportation barriers, social isolation, financial strain — from clinical narrative and maps the spans to ICD-10-CM Z-codes (Z55–Z65). Use after running OpenMed NER when the user wants SDOH surfacing, Z-code suggestion, health-equity analytics, or to recover SDOH that is documented in free text but not coded. Pairs with OpenMed analyze_text output. Standards: ICD-10-CM Z55–Z65, Gravity Project value sets, n2c2 2022 SDOH track. Trigger keywords: SDOH, social determinants, Z-codes, housing, food

Data & Analytics · maziyarpanahi/openmed

Generate a model card for an OpenMed clinical NER or de-identification model documenting intended use, quantitative metrics, subgroup performance, limitations, and a medical-device disclaimer for clinical AI governance. Use when the user wants to write or update a model card, a README model section, or governance documentation, or to turn OpenMed eval outputs (release gate report, fairness_report, error_report) into the card's metrics and limitations sections. Trigger on \"model card\", \"intended use\", \"model documentation\", \"governance\", \"limitations section\", \"datasheet\", or \"FDA/

Documentation · maziyarpanahi/openmed

Score an OpenMed clinical or biomedical NER model against a user-supplied gold corpus with entity-level precision, recall, and F1, then break errors down per label. Use when the user wants a seqeval-style scorecard, strict vs partial (relaxed) span matching, a per-label confusion matrix, false-negative / false-positive examples, or to debug why a model misses entities. Trigger on \"evaluate NER\", \"entity-level F1\", \"seqeval\", \"precision recall F1\", \"confusion matrix\", \"error analysis\", \"strict vs partial match\", or \"score against gold\" in an OpenMed context. The gold corpus is u

Code Review & Quality · maziyarpanahi/openmed

Benchmark an OpenMed PII model with synthetic gold spans and report label-aware exact-span and grapheme recall without emitting identifier surfaces. Use when an agent must compare a model, threshold, backend, or quantized artifact and enforce a recall floor before release.

Backend & API · maziyarpanahi/openmed

Produce a signed, reproducible, no-PHI audit trail for an OpenMed de-identification run via deidentify(audit=True). Use when the user needs compliance evidence, a tamper-evident record of what was redacted and why, to verify nothing was changed, to retain proof for HIPAA/GDPR audits, or to review de-id decisions without exposing plaintext PHI. Covers the AuditReport / AuditSignature / AuditSpan / DetectorInfo fields, why audits store offsets+hashes+provenance+residual-risk and never plaintext, signing with .sign(key), and verifying with .verify(key). Pairs with OpenMed deidentifying-clinical-t

Security · maziyarpanahi/openmed

Orient and bootstrap any project that uses OpenMed, the on-device clinical and biomedical NLP library, for named-entity recognition, PHI de-identification, FHIR export, and evaluation. Use when the user mentions OpenMed, wants to install it, asks which OpenMed capability or model fits a task, or is starting to build a clinical/medical text pipeline and needs the right entry point.

Workflow & Productivity · maziyarpanahi/openmed

Assemble a chronological patient timeline from OpenMed-extracted clinical events, normalizing dates and resolving relative time expressions on-device. Use when the user wants to build a patient timeline, order events from clinical notes, reconstruct a longitudinal history, plot a course of illness, or turn analyze_text/deidentify output into a sorted sequence of dated encounters, diagnoses, medications, and procedures. Covers temporal normalization (absolute and relative), event modeling toward FHIR Encounter/Condition.onsetDateTime, anchoring to a document/admission date, and handling undated

Other · maziyarpanahi/openmed