Deidentifying Multilingual Text
De-identify non-English clinical text on-device with OpenMed by passing lang= and...
Install
npx skills add maziyarpanahi/openmed --skill deidentifying-multilingual-text -g -a claude-code -y- Repository
- maziyarpanahi/openmed5.8k
- Category
- Writing
- Updated
- 4d ago
- License
- Apache-2.0
- Context cost
- Lightabout 1,491 tokens
- Runs scripts
- No, instructions only
What it does
De-identify non-English clinical text on-device with OpenMed by passing lang= and locale= to deidentify(). Use when the user has Spanish, German, French, Italian, Portuguese, Dutch, Hindi, Telugu, Arabic, Japanese, or Turkish medical notes, needs locale-aware fake surrogates, must handle language-specific national IDs (DNI, NIR, Steuer-ID, codice fiscale, BSN, CPF, TCKN, Aadhaar), or asks which languages OpenMed PII supports. Covers SUPPORTED_LANGUAGES, get_pii_models_by_language, get_patterns_for_language, LANG_TO_LOCALE, and accent normalization. Pairs with OpenMed deidentifying-clinical-text and generating-synthetic-surrogates.
De-identifying multilingual text
OpenMed de-identifies clinical text in many languages, each with a dedicated
PII model, language-specific regex patterns (national IDs, phone formats), and a
locale-aware surrogate generator. Pass lang= to deidentify / extract_pii
and the right model, patterns, and fake-data tables are selected automatically.
Everything runs on-device.
When to use this skill
Use it whenever the source text is not English, or when surrogates must look native to the locale (a German note should get German-looking fake names and a valid-format Steuer-ID surrogate, not a US SSN).
Discover supported languages at runtime, don't hardcode
import openmed
from openmed.core.pii_i18n import SUPPORTED_LANGUAGES, get_patterns_for_language
print(sorted(SUPPORTED_LANGUAGES)) # query it; the set is the source of truth
# Language-appropriate default model for a code:
models = openmed.get_pii_models_by_language("es")
# Language-specific regex patterns (national IDs, phones, etc.):
patterns = get_patterns_for_language("de")
The set currently spans English plus European, South Asian, Middle Eastern, and
East Asian languages, but always read SUPPORTED_LANGUAGES rather than
trusting a number, since it changes as models ship. MCP exposes the same list
via openmed_list_pii_languages.
Quick start (Spanish)
import openmed
nota = (
"El paciente Carlos Hernández (DNI 12345678Z), nacido el 11/04/1979, "
"vive en Calle Mayor 5, Madrid. Teléfono 612 345 678."
)
result = openmed.deidentify(
nota,
lang="es", # selects the Spanish PII model + ES patterns
method="replace", # locale-native fake values
locale="es_ES", # Faker locale (defaults from lang via LANG_TO_LOCALE)
)
print(result.deidentified_text)
# El paciente [surrogate name] (DNI [surrogate]), nacido el [date], ...
For German, just switch the code:
