app/post_processor.py

NEGATIVE_TERMS = ['clear', 'normal', 'unremarkable', 'no', 'negative', 'absent', 'within normal limits', 'stable']
POSITIVE_TERMS = ['opacity', 'infiltrate', 'consolidation', 'fracture', 'abnormal', 'effusion', 'edema', 'pneumothorax', 'cardiomegaly', 'mass', 'nodule', 'atelectasis']
CRITICAL_TERMS = ['acute', 'severe', 'large', 'extensive', 'pneumothorax', 'fracture', 'mass', 'suspicious']

MEDICAL_GLOSSARY = {
    'pulmonary edema': 'Fluid buildup in the lungs, making breathing difficult',
    'focal consolidation': 'Dense area in lung tissue, possibly indicating infection',
    'pleural effusion': 'Fluid accumulation around the lungs',
    'pneumothorax': 'Collapsed lung due to air leak',
    'cardiomegaly': 'Enlarged heart',
    'opacity': 'Cloudy area on X-ray, may indicate infection or fluid',
    'infiltrate': 'Abnormal substance in lung tissue',
    'atelectasis': 'Partial lung collapse',
    'nodule': 'Small round growth in the lung',
    'mass': 'Larger abnormal tissue growth requiring investigation',
    'consolidation': 'Area where air spaces are filled with fluid or tissue',
    'effusion': 'Abnormal fluid collection'
}

def structure_entities(entities):
    anatomy_entities = []
    observation_entities = []
    positive_findings = []
    negative_findings = []
    critical_findings = []
    
    for entity in entities:
        if entity['label'] == 'ANATOMY':
            anatomy_entities.append(entity['text'])
        elif entity['label'] == 'OBSERVATION':
            observation_entities.append(entity['text'])
            
            obs_lower = entity['text'].lower()
            
            is_critical = any(term in obs_lower for term in CRITICAL_TERMS)
            is_negative = any(term in obs_lower for term in NEGATIVE_TERMS)
            is_positive = any(term in obs_lower for term in POSITIVE_TERMS)
            
            if is_critical:
                critical_findings.append(entity['text'])
            elif is_negative:
                negative_findings.append(entity['text'])
            elif is_positive:
                positive_findings.append(entity['text'])
    
    return {
        'anatomy': list(set(anatomy_entities)),
        'all_observations': observation_entities,
        'positive_findings': list(set(positive_findings)),
        'negative_findings': list(set(negative_findings)),
        'critical_findings': list(set(critical_findings))
    }

def generate_summary(structured):
    total_entities = len(structured['anatomy']) + len(structured['all_observations'])
    anatomy_count = len(structured['anatomy'])
    observations_count = len(structured['all_observations'])
    has_critical = len(structured['critical_findings']) > 0
    has_abnormalities = len(structured['positive_findings']) > 0
    
    return {
        'total_entities': total_entities,
        'anatomy_count': anatomy_count,
        'observations_count': observations_count,
        'has_critical_findings': has_critical,
        'has_abnormalities': has_abnormalities
    }

def generate_patient_friendly_summary(structured):
    summary = {
        'overall_status': '',
        'key_findings': [],
        'areas_of_concern': [],
        'next_steps': [],
        'explanation': ''
    }
    
    total_abnormalities = len(structured['positive_findings'])
    total_critical = len(structured['critical_findings'])
    
    if total_critical > 0:
        summary['overall_status'] = 'URGENT ATTENTION REQUIRED'
        summary['explanation'] = 'Your X-ray shows findings that need immediate medical attention. Please contact your doctor right away.'
    elif total_abnormalities > 0:
        summary['overall_status'] = 'ABNORMALITIES DETECTED'
        summary['explanation'] = 'Your X-ray shows some areas of concern that should be discussed with your doctor. This does not necessarily mean a serious problem, but follow-up is recommended.'
    else:
        summary['overall_status'] = 'NO MAJOR CONCERNS'
        summary['explanation'] = 'Your chest X-ray appears normal with no significant abnormalities detected. Continue regular health maintenance.'
    
    for finding in structured['positive_findings']:
        finding_lower = finding.lower()
        explanation = None
        
        for term, desc in MEDICAL_GLOSSARY.items():
            if term in finding_lower:
                explanation = desc
                break
        
        summary['key_findings'].append({
            'finding': finding,
            'explanation': explanation if explanation else 'Please consult your doctor for clarification on this finding'
        })
    
    for critical in structured['critical_findings']:
        critical_lower = critical.lower()
        explanation = None
        
        for term, desc in MEDICAL_GLOSSARY.items():
            if term in critical_lower:
                explanation = desc
                break
        
        summary['areas_of_concern'].append({
            'finding': critical,
            'explanation': explanation if explanation else 'This requires immediate medical evaluation',
            'severity': 'HIGH'
        })
    
    if total_critical > 0:
        summary['next_steps'] = [
            'Contact your doctor immediately',
            'Do not delay seeking medical attention',
            'Bring this report to your appointment',
            'Follow all recommended treatments'
        ]
    elif total_abnormalities > 0:
        summary['next_steps'] = [
            'Schedule a follow-up with your doctor within 1-2 weeks',
            'Additional tests or imaging may be recommended',
            'Discuss treatment options if needed',
            'Monitor for any new or worsening symptoms'
        ]
    else:
        summary['next_steps'] = [
            'Maintain regular health check-ups',
            'Continue healthy lifestyle practices',
            'Report any new respiratory symptoms to your doctor',
            'Follow recommended screening schedules'
        ]
    
    return summary

def generate_recommendations(structured):
    recommendations = []
    
    if len(structured['critical_findings']) > 0:
        recommendations.append("Immediate medical consultation required")
        recommendations.append("Consider emergency department visit if symptomatic")
    
    if len(structured['positive_findings']) > 0:
        recommendations.append("Follow-up imaging may be needed")
        recommendations.append("Consult with a pulmonologist or radiologist")
    
    if 'pneumothorax' in ' '.join(structured['positive_findings']).lower():
        recommendations.append("Urgent evaluation for possible chest tube placement")
    
    if 'mass' in ' '.join(structured['positive_findings']).lower() or 'nodule' in ' '.join(structured['positive_findings']).lower():
        recommendations.append("CT scan recommended for further evaluation")
        recommendations.append("Consider biopsy if clinically indicated")
    
    if 'effusion' in ' '.join(structured['positive_findings']).lower():
        recommendations.append("Consider thoracentesis if symptomatic")
    
    if len(structured['critical_findings']) == 0 and len(structured['positive_findings']) == 0:
        recommendations.append("Continue routine health maintenance")
        recommendations.append("Repeat imaging only if clinically indicated")
    
    return recommendations