feat: mode Validation DIM dans le viewer Flask
Permet aux médecins DIM de valider/corriger les codes CIM-10 extraits par le pipeline pour construire un gold standard (50 dossiers). - ValidationManager : gestion annotations JSON dans data/gold_standard/ - Script sélection 50 dossiers (25 CPAM + 25 stratifiés CMD/confiance) - Routes /validation, /api/cim10/search, /api/validation/save, /validation/metrics - Formulaire avec autocomplete CIM-10, boutons Correct/Modifier/Supprimer - Dashboard métriques : precision, recall, F1, hallucination par confiance/source Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
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scripts/select_validation_dossiers.py
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scripts/select_validation_dossiers.py
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#!/usr/bin/env python3
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"""Sélectionne 50 dossiers pour le gold standard de validation DIM.
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- 25 dossiers CPAM (cas complexes, déjà contrôlés)
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- 25 dossiers non-CPAM stratifiés par CMD, confiance DP, nombre de DAS
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Crée data/gold_standard/_selection.json et initialise les annotations vides.
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"""
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from __future__ import annotations
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import json
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import random
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import sys
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from pathlib import Path
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# Ajouter le répertoire racine au path
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sys.path.insert(0, str(Path(__file__).resolve().parent.parent))
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from src.config import STRUCTURED_DIR, BASE_DIR, DossierMedical
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GOLD_DIR = BASE_DIR / "data" / "gold_standard"
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TARGET_TOTAL = 50
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TARGET_CPAM = 25
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def load_all_dossiers() -> list[dict]:
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"""Charge tous les dossiers fusionnés depuis output/structured/."""
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dossiers = []
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for subdir in sorted(STRUCTURED_DIR.iterdir()):
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if not subdir.is_dir():
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continue
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# Chercher le fichier fusionné
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fusionne = None
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for f in subdir.glob("*fusionne*.json"):
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fusionne = f
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break
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if not fusionne:
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# Prendre le premier JSON du dossier
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jsons = sorted(subdir.glob("*.json"))
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if jsons:
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fusionne = jsons[0]
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if not fusionne:
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continue
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try:
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data = json.loads(fusionne.read_text(encoding="utf-8"))
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dossier = DossierMedical.model_validate(data)
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rel_path = str(fusionne.relative_to(STRUCTURED_DIR))
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group_name = subdir.name
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dossiers.append({
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"dossier_id": f"{group_name}/{fusionne.stem}",
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"group_name": group_name,
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"path_rel": rel_path,
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"dossier": dossier,
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})
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except Exception as e:
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print(f" Erreur chargement {fusionne.name}: {e}")
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return dossiers
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def select_dossiers(all_dossiers: list[dict]) -> list[dict]:
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"""Sélectionne les 50 dossiers selon la stratégie définie."""
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# Séparer CPAM / non-CPAM
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cpam = [d for d in all_dossiers if d["dossier"].controles_cpam]
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non_cpam = [d for d in all_dossiers if not d["dossier"].controles_cpam]
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print(f"Dossiers CPAM disponibles : {len(cpam)}")
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print(f"Dossiers non-CPAM disponibles : {len(non_cpam)}")
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# Prendre tous les CPAM (ou max TARGET_CPAM)
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selected_cpam = cpam[:TARGET_CPAM]
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remaining_target = TARGET_TOTAL - len(selected_cpam)
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# Stratifier les non-CPAM
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selected_non_cpam = stratified_sample(non_cpam, remaining_target)
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selected = selected_cpam + selected_non_cpam
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print(f"\nSélection finale : {len(selected)} dossiers")
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print(f" - CPAM : {len(selected_cpam)}")
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print(f" - Non-CPAM : {len(selected_non_cpam)}")
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return selected
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def stratified_sample(dossiers: list[dict], n: int) -> list[dict]:
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"""Échantillonnage stratifié par CMD, confiance DP et nombre de DAS."""
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if len(dossiers) <= n:
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return dossiers
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# Grouper par CMD
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by_cmd: dict[str, list[dict]] = {}
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for d in dossiers:
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ghm = d["dossier"].ghm_estimation
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cmd = ghm.cmd if ghm else "inconnu"
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by_cmd.setdefault(cmd or "inconnu", []).append(d)
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selected = []
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seen_ids = set()
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# Phase 1 : 1 dossier par CMD (diversité maximale)
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cmds = sorted(by_cmd.keys())
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random.seed(42) # Reproductible
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for cmd in cmds:
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if len(selected) >= n:
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break
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candidates = by_cmd[cmd]
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# Préférer un mix de confiances
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random.shuffle(candidates)
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d = candidates[0]
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selected.append(d)
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seen_ids.add(d["dossier_id"])
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# Phase 2 : compléter avec diversité confiance DP
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if len(selected) < n:
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remaining = [d for d in dossiers if d["dossier_id"] not in seen_ids]
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# Trier par confiance DP (low > medium > high pour surreprésenter les cas difficiles)
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conf_order = {"low": 0, "medium": 1, "high": 2, None: 3}
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remaining.sort(key=lambda d: (
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conf_order.get(
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d["dossier"].diagnostic_principal.cim10_confidence
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if d["dossier"].diagnostic_principal else None,
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3
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),
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-len(d["dossier"].diagnostics_associes), # beaucoup de DAS d'abord
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))
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for d in remaining:
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if len(selected) >= n:
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break
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selected.append(d)
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return selected[:n]
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def create_empty_annotation(dossier_id: str, dossier: DossierMedical) -> dict:
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"""Crée une annotation vide pour un dossier."""
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dp = dossier.diagnostic_principal
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das_list = []
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for i, das in enumerate(dossier.diagnostics_associes):
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das_list.append({
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"index": i,
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"texte_original": das.texte,
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"code_pipeline": das.cim10_suggestion or "",
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"confidence": das.cim10_confidence or "",
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"source": das.source or "",
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"statut": "correct",
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"code_corrige": None,
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"commentaire": "",
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})
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return {
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"dossier_id": dossier_id,
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"validateur": "",
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"date_validation": "",
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"statut": "non_commence",
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"dp": {
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"texte_original": dp.texte if dp else "",
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"code_pipeline": dp.cim10_suggestion if dp else "",
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"confidence": dp.cim10_confidence if dp else "",
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"statut": "correct",
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"code_corrige": None,
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"commentaire": "",
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},
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"das": das_list,
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"das_ajoutes": [],
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"commentaire_general": "",
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}
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def main():
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print("=== Sélection des dossiers pour validation DIM ===\n")
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all_dossiers = load_all_dossiers()
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print(f"Total dossiers chargés : {len(all_dossiers)}\n")
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if not all_dossiers:
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print("Aucun dossier trouvé dans output/structured/")
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sys.exit(1)
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selected = select_dossiers(all_dossiers)
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# Créer le répertoire gold standard
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GOLD_DIR.mkdir(parents=True, exist_ok=True)
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# Sauvegarder la sélection
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selection = {
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"date_selection": __import__("datetime").datetime.now().isoformat(timespec="seconds"),
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"total": len(selected),
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"cpam": sum(1 for d in selected if d["dossier"].controles_cpam),
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"non_cpam": sum(1 for d in selected if not d["dossier"].controles_cpam),
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"dossiers": [d["dossier_id"] for d in selected],
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}
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selection_path = GOLD_DIR / "_selection.json"
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selection_path.write_text(
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json.dumps(selection, ensure_ascii=False, indent=2),
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encoding="utf-8",
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)
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print(f"\nSélection sauvegardée : {selection_path}")
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# Initialiser les annotations vides
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created = 0
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for d in selected:
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dossier_id = d["dossier_id"]
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safe_name = dossier_id.replace("/", "__") + ".json"
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annot_path = GOLD_DIR / safe_name
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if not annot_path.exists():
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annotation = create_empty_annotation(dossier_id, d["dossier"])
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annot_path.write_text(
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json.dumps(annotation, ensure_ascii=False, indent=2),
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encoding="utf-8",
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)
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created += 1
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print(f"Annotations vides créées : {created}")
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print(f"Annotations existantes préservées : {len(selected) - created}")
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# Résumé
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print(f"\n--- Résumé ---")
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for i, d in enumerate(selected, 1):
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dos = d["dossier"]
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dp_code = dos.diagnostic_principal.cim10_suggestion if dos.diagnostic_principal else "?"
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dp_conf = (dos.diagnostic_principal.cim10_confidence or "?") if dos.diagnostic_principal else "?"
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n_das = len(dos.diagnostics_associes)
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cpam_flag = " [CPAM]" if dos.controles_cpam else ""
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ghm = dos.ghm_estimation
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cmd = ghm.cmd if ghm else "?"
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print(f" {i:2d}. {d['group_name']:<20s} DP={dp_code:<6s} conf={dp_conf:<7s} DAS={n_das:2d} CMD={cmd}{cpam_flag}")
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if __name__ == "__main__":
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main()
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