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import json
from typing import Dict, Any, List
# --- Pre-compiled Medical Knowledge Base (Simulated) ---
# In a real application, this would be a large database (e.g., SQL, MongoDB, or specialized API)
MEDICAL_KNOWLEDGE_BASE = {
"Comminuted": {
"definition": "A fracture where the bone is broken into three or more pieces.",
"icd_code": "S52.5",
"severity": "High",
"treatment_guidelines": ["Usually requires surgical intervention (ORIF - Open Reduction Internal Fixation).", "Long immobilization time (8-12 weeks).", "Requires physical therapy."],
"prognosis_notes": "Risk of non-union is higher. Full recovery may take 6+ months."
},
"Greenstick": {
"definition": "A partial fracture where the bone is cracked but not completely broken through. Common in children.",
"icd_code": "S52.3",
"severity": "Low-Moderate",
"treatment_guidelines": ["Immobilization with cast or splint.", "Careful monitoring for progression.", "Minimal surgical intervention usually needed."],
"prognosis_notes": "Generally good prognosis. Recovery typically within 4-6 weeks."
},
"Healthy": {
"definition": "No evidence of fracture. Bone appears normal.",
"icd_code": "Z00.0",
"severity": "None",
"treatment_guidelines": ["No treatment required.", "Continue normal activities as tolerated.", "Regular follow-up if there is persistent pain."],
"prognosis_notes": "Normal bone health. No intervention needed."
},
"Oblique": {
"definition": "A diagonal break across the bone at approximately 45 degrees.",
"icd_code": "S52.2",
"severity": "Moderate",
"treatment_guidelines": ["Immobilization with cast or splint.", "Regular X-rays to monitor healing.", "Physical therapy after immobilization period."],
"prognosis_notes": "Good prognosis with proper immobilization. Recovery typically 6-8 weeks."
},
"Oblique Displaced": {
"definition": "A diagonal break where the bone fragments are not aligned and have shifted out of place.",
"icd_code": "S52.9",
"severity": "Medium-High",
"treatment_guidelines": ["Requires reduction (closed or open).", "Often requires casting or sometimes surgery to stabilize.", "Regular X-rays to ensure proper alignment."],
"prognosis_notes": "Good prognosis if successfully reduced and stabilized. Recovery 8-12 weeks."
},
"Spiral": {
"definition": "A twisting break that spirals around the bone, typically caused by rotational forces.",
"icd_code": "S52.4",
"severity": "Serious",
"treatment_guidelines": ["Usually requires immobilization in a cast or brace.", "May require surgery if fragments are unstable.", "Requires extensive physical therapy."],
"prognosis_notes": "Variable recovery time. May take 8-16 weeks depending on severity."
},
"Transverse": {
"definition": "A clean break straight across the bone, perpendicular to the bone's long axis.",
"icd_code": "S52.1",
"severity": "Moderate",
"treatment_guidelines": ["Immobilization with cast or splint.", "Regular X-rays to monitor alignment.", "Physical therapy after healing begins."],
"prognosis_notes": "Good prognosis. Clean breaks typically heal well. Recovery 6-10 weeks."
},
"Transverse Displaced": {
"definition": "A straight break across the bone with fragments shifted out of place.",
"icd_code": "S52.8",
"severity": "Serious",
"treatment_guidelines": ["Requires reduction (closed or open).", "Often requires surgery to realign fragments.", "Long-term immobilization and rehabilitation."],
"prognosis_notes": "Good prognosis with treatment. Recovery 10-14 weeks."
}
}
class KnowledgeAgent:
def __init__(self, knowledge_base: Dict[str, Any]):
self.knowledge_base = knowledge_base
def get_medical_summary(self, diagnosis: str, confidence: float) -> Dict[str, Any]:
"""
Retrieves and formats external medical knowledge based on the final diagnosis.
"""
diagnosis = diagnosis.strip()
if diagnosis not in self.knowledge_base:
return {"error": "Diagnosis not found in the knowledge base."}
# 1. Retrieve Raw Data
raw_data = self.knowledge_base[diagnosis]
# 2. Format Summary for Professional Use (Example output)
summary = {
"Diagnosis": diagnosis,
"Ensemble_Confidence": f"{confidence:.2f}",
"Type": raw_data.get("definition"),
"ICD_Code": raw_data.get("icd_code", "N/A"),
"Severity": raw_data.get("severity"),
"Guidelines": raw_data.get("treatment_guidelines")
}
return summary
# --- Example Usage (Integration with Cross-Validation Agent Output) ---
if __name__ == '__main__':
# Assume this is the output from your cross_validation_agent:
cross_validation_result = {
"ensemble_prediction": "Oblique Displaced",
"ensemble_confidence": 0.85
}
agent = KnowledgeAgent(MEDICAL_KNOWLEDGE_BASE)
medical_report = agent.get_medical_summary(
diagnosis=cross_validation_result["ensemble_prediction"],
confidence=cross_validation_result["ensemble_confidence"]
)
print("\n--- 🧠 KNOWLEDGE AGENT REPORT ---")
print(json.dumps(medical_report, indent=4)) |