Diagnostic Agent
Multi-hypothesis differential diagnosis with Bayesian reasoning
Model: proofmed-diagnostic-v4
Multi-hypothesis differential diagnosis
Bayesian probability calculation
Pattern recognition across 8,000+ conditions
Diagnostic Agent Inference
Model Loaded • Ready
Analysis Output
Waiting for input...
This agent can:
→ Multi-hypothesis differential diagnosis
→ Bayesian probability calculation
→ Pattern recognition across 8,000+ conditions
→ Rare disease detection
→ Symptom clustering analysis
Available Tools
Symptom Analyzer
Lab Value Interpreter
Physical Exam Findings
Medical History Analyzer
Differential Ranker
Zebra Detector (Rare Diseases)
Technical Specifications
Model: proofmed-diagnostic-v4
Parameters: 7B fine-tuned
Latency: <200ms
Accuracy: 99.2%
Training Data: 50M+ medical records
Integration Options
# API Integration
import proofmed
agent = proofmed.DiagnosticAgent()
result = agent.analyze({
"input": patient_data,
"mode": "comprehensive"
})
print(result.diagnosis)Evidence Base
PubMed: 30M+ papers indexed
Guidelines: 500+ clinical guidelines
Trials: 100K+ RCTs analyzed
Updates: Real-time literature monitoring