resolving-clinical-context
Assign negation, temporality, and uncertainty (the ConText axes) to clinical entities extracted by OpenMed, so \"denies chest pain\" is not counted as chest pain and \"history of MI\" is not counted as an active MI. Use after NER when the user needs assertion status, negation detection, family-history / hypothetical / historical flags, or ConText/NegEx-style classification before grounding entities to FHIR or a problem list. Covers openmed.clinical.resolve_negation / resolve_temporality / resolve_uncertainty / resolve_span_context / assert_context_axes, ClinicalAssertion, and the AFFIRMED/NEGA
npx skills add maziyarpanahi/openmed --skill resolving-clinical-context --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Resolving clinical context NER finds *that* a condition was mentioned; it does not tell you whether the patient **has** it. "Patient denies chest pain," "history of MI," and "rule out PE" all surface entities that must **not** be recorded as active, present findings. OpenMed's `openmed.clinical` ConText layer assigns three deterministic axes to each span — **negation**, **temporality**, **uncertainty** — turning raw mentions into clinically faithful assertions before they reach a problem list or FHIR Condition. ## When to use - Immediately after `extracting-clinical-entities`, before grounding, problem-list building, or analytics. - The user asks for assertion status, negation handling, "is this affirmed?", family-history vs. patient, historical vs. active, or hedged/uncertain findings. - You are about to map entities to FHIR `verificationStatus` /`clinicalStatus` and need the upstream signal. ## Quick start ```python import openmed from openmed.clinical import ( resolve_span_context, assert_context_axes, NEGATED, HISTORICAL, HYPOTHETICAL, UNCERTAIN, ) note = "Patient denies chest pain. History of MI. Concern for PE; rule out DVT." # 1) Extract entities (registry key, HF id, or l
- When to use
- Quick start
- Workflow
- Hand-off to / from OpenMed
- Edge cases & gotchas
- Standards & references
What does the resolving-clinical-context skill do?
Assign negation, temporality, and uncertainty (the ConText axes) to clinical entities extracted by OpenMed, so \"denies chest pain\" is not counted as chest pain and \"history of MI\" is not counted as an active MI. Use after NER when the user needs assertion status, negation detection, family-history / hypothetical / historical flags, or ConText/NegEx-style classification before grounding entities to FHIR or a problem list. Covers openmed.clinical.resolve_negation / resolve_temporality / resolve_uncertainty / resolve_span_context / assert_context_axes, ClinicalAssertion, and the AFFIRMED/NEGA
How do I install it?
Run `npx skills add maziyarpanahi/openmed --skill resolving-clinical-context --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From maziyarpanahi/openmed, a repository with 4,851 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.