Files
anonymisation/tests/ground_truth/annotations/001_simple_unknown_BACTERIO_23018396.json
Domi31tls ee34042179 feat: Optimize EPISODE false positives - filter trackare filename episodes
- Modified detectors/hospital_filter.py:
  * Updated is_episode_in_filename() to only filter trackare documents
  * Pattern: trackare-XXXXXXXX-YYYYYYYY where YYYYYYYY is episode number
  * Prevents filtering legitimate episodes in CRH/CRO documents

- Modified anonymizer_core_refactored_onnx.py:
  * Filter page=-1 entries (global propagation) from audit file
  * These are internal replacement tokens, not real detections

- Modified evaluation/quality_evaluator.py:
  * Fixed load_annotations() to use ground_truth_dir instead of pdf_path.parent
  * Added support for 'pages' format from auto-annotation script
  * Converts 'pages' format to 'annotations' format automatically

- Updated test dataset annotations with hospital filter applied

Results:
- EPISODE: Precision 100% (was 14.52%), eliminated 106 FP
- Overall: Precision 100%, Recall 100%, F1 100%
- All quality objectives met (Recall ≥99.5%, Precision ≥97%, F1 ≥98%)
2026-03-02 15:33:29 +01:00

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JSON

{
"pdf_path": "001_simple_unknown_BACTERIO_23018396.pdf",
"total_pages": 1,
"annotated_by": "auto-annotation-v1",
"annotation_date": "2026-03-02",
"pages": [
{
"page_number": 0,
"pii": {
"ETABLISSEMENT": [
"Centre Hospitalier de la Côte Basque"
],
"NOM": [
"JAOUEN Anne-Christine",
"MENARD-DEROURE Fanny",
"LEYSSENE David Dr",
"CURUTCHET-BURTIN Marie-Laure Dr",
"SEGUES Rémi Dr",
"SABATIER Pierre Dr",
"Pierre SABATIER ACCRED"
],
"IPP": [
"23000862"
]
}
}
]
}