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AI-Driven EHR Systems: Comparative Analysis (2020-2025)
Five key studies showing diverse approaches to smart health records
Study (Short Title)
Main Focus
Architecture Layers
AI Roles
Strengths
Limitations
جریان داده
جریان داده
جریان داده
جریان داده
AI-Driven Optimization
Predictive Analytics & Workflow
Data Sources/EHR/


Edge/Analytics

NLP, ML prediction, XAI
Comprehensive conceptual model
Lacks clinical validation
AI-Blockchain EHR SLR
Security & Privacy
Blockchain + AI integration
Fraud detection, anomaly
Systematic review, taxonomy
Scalability issues
Multimodal Framework
Data Integration
Ingestion/FHIR/


Harmonized

NLP, causal models, SHAP
Detailed layered architecture
No implementation
Elastic EHR 5-Tier
UX & Flexibility
5-tier user-centric
Adaptive UI, personalization
Clinician experience focus
Limited technical depth
EHR 2025 Trends
Future Trends
Cloud/AI/Patient-centric
AI scribes, automation
Forward-looking
Descriptive only
معماری لایه‌ای سوابق سلامت هوشمند
معماری پنج لایه‌ای بر اساس مطالعات بررسی‌شده
لایه کاربردها .۵


(CDS Dashboards, Patient Apps, Governance)

لایه تحلیلی AI .۴


(NLP, ML Prediction, XAI, Causal Models)

مخزن داده یکپارچه .۳


(Data Lake/Warehouse)

لایه یکپارچه‌سازی .۲


(FHIR/SMART, ETL, Audit Trails)

منابع داده .۱


(EHR, Wearables, Mobile Apps, PROs)

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by mooji

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