Unstructured Medical Text Miner

from skills.unstructured_medical_text_miner.scripts.main import MedicalTextMiner
Initialize miner
miner = MedicalTextMiner()
Load MIMIC-IV note data
miner.load_notes(notes_path="path/to/noteevents.csv")
Extract all text records for a specific patient
patient_texts = miner.get_patient_texts(subject_id=10000032)
Execute complete information extraction
insights = miner.extract_insights(
    text=patient_texts,
    extract_entities=True,
    extract_relations=True,
    extract_timeline=True
)

config.yaml
extraction:
  entity_types: ["DISEASE", "SYMPTOM", "MEDICATION", "PROCEDURE", "ANATOMY"]
  relation_types: ["TREATS", "CAUSES", "CONTRAINDICATED_WITH"]
  enable_negation_detection: true
  
models:
  ner_model: "en_core_sci_lg"  # or "en_core_sci_scibert"
  relation_model: "custom_relation_extractor"
  
output:
  format: "json"  # json/fhir/kg
  include_raw_text: false