Intelligent Diagnosis System
An AI-assisted diagnosis, treatment recommendation, and clinical pathway management system built on medical large models, delivering real-time, explainable AI support for clinical decisions.
Overview
The Intelligent Diagnosis System is the core AI application that connects medical knowledge with clinical practice. We deeply integrate cutting-edge large-model technology with clinical guidelines, drug knowledge bases, and real-world clinical data to help medical institutions build AI-assisted diagnosis, treatment recommendation, and clinical pathway management systems — giving every clinician reliable AI-assisted decision support.
Core Capabilities
1. Diagnostic Assistance Engine
- Fuses multi-source clinical data and performs differential-diagnosis reasoning based on a medical knowledge graph
- Recommends further examinations, annotating the clinical significance and evidence basis of each test
- Assists rare-disease screening to narrow the differential diagnosis
- Integrates in real time with hospital HIS/EMR, embedding seamlessly into the physician workstation
2. Treatment Recommendation
- Recommends individualized treatment plans based on the latest clinical guidelines and drug knowledge bases
- Automatically annotates the level of evidence for each recommendation (Class I / IIa / IIb / III)
- Real-time drug-interaction checks, dosage-adjustment suggestions, and allergy/contraindication alerts
- Quantifies and compares the risk–benefit of treatment options
3. Clinical Pathway Management
- Digitizes clinical pathways, automatically triggering smart prompts at each care node
- Abnormal-indicator alerts: proactively notifies when lab results deviate from expectations
- Mandatory confirmation at critical nodes (surgical checklists, critical-value handling, etc.)
- Pathway variance analysis and visualized monitoring of quality indicators
4. Continuous Knowledge Updates
- Automatically tracks the latest domestic and international guideline updates and pushes key changes
- Retrospective analysis of in-hospital care quality with improvement suggestions
- Evidence-based discussion support for complex cases
Typical Application
A tertiary hospital deployed the Intelligent Diagnosis System in its endocrinology department, integrating international diabetes guidelines (ADA, CDS, etc.) with 20,000 electronic medical records. The system analyzes outpatient data in real time to support treatment-plan optimization. Six months after deployment, the department’s glycemic control rate rose from 62% to 78%.
Technical Advantages
| Dimension | Traditional HIS/CDSS | Simo Intelligent Diagnosis System |
|---|---|---|
| Knowledge updates | Manual item-by-item maintenance | AI auto-tracks the latest guidelines |
| Decision basis | Fixed-rule triggering | Guideline evidence + local-data reasoning |
| Explainability | Black-box output | Item-level annotation of evidence source and level |
| Personalization | Generic templates | Combines full-dimensional patient data |
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