AI-Powered
Cardiovascular
Digital Twin Model
We process electronic health record data and provide healthcare organizers with unique analytics generated via LLM-enabled chat, aimed at preventing adverse events (Myocardial Infarction, Heart attack, Stroke) in every cardiovascular patient
Multi-Agent MCP Approach to Automate Data Processing
✜ Easy to use for relevant clinical information search inside EHR
✜ Enhancing the LLM Assistant for Smarter Patient Data Collection
✜ List of Patients for Follow-Up Recommendations & Proactive Management of At-Risk Patients
✜ EMR data with simple upload via MCP server and seamless integration with host clients
✜ Enhancing the LLM Assistant for Smarter Patient Data Collection
✜ List of Patients for Follow-Up Recommendations & Proactive Management of At-Risk Patients
✜ EMR data with simple upload via MCP server and seamless integration with host clients
✜ An invaluable tool for primary care practitioners that supports them in prescribing the most effective treatment with evidence-based principles and real-world data
✜ Preparation of interactive analytical dashboards for comprehensive overview and generation of individual reports for proactive management
The eMed Support digital twin enables a patient-centric and value-based approach throughout every stage of the care continuum
✜ Screening, Identification of high-risk patients and diagnosis
✜ Early detection with AI-prediction of LDL-C level and GFR
✜ Personalized treatment recommendation according to clinical guidelines and CV risks prognosis based on prescribed therapy
✜ Therapy progress monitoring with treatment goals achievement tracking
✜ Disease management through hospitalization and adverse events prevention
✜ Early detection with AI-prediction of LDL-C level and GFR
✜ Personalized treatment recommendation according to clinical guidelines and CV risks prognosis based on prescribed therapy
✜ Therapy progress monitoring with treatment goals achievement tracking
✜ Disease management through hospitalization and adverse events prevention
AI-POWERED CLINICAL DATA PROCESSING FOR:
- HEALTH AUTHORITIES
Quality of medical care improvement and costs reduction✜ Risk assessment for identification of patients not achieving treatment goalsConnect eMed Support
✜ AI prediction of indicators missing in the EHR and selection of patients with prognostic deviations in LDL-C, EF and GFR
✜ Management of high-risk chronic CV patients through treatment strategy recommendation for optimal goals treatment achievement - PUBLIC AND PRIVATE CLINICS
+30% additional consultations and tests for treatment target achievement✜ Automatization of EHRs analysis for tracking of chronic patients' treatment goals achievement and optimal routing to GP or cardiologistTest eMed Support
✜ Enhancement of heart health check-ups with digital cardiovascular assessment
✜ Reduction of GP's time for 120+ patient characteristics assessment to 1 min vs 40 min, enabling high-quality communication with patient
✜ Accurate medicine procurement planning taking into account evidence-based treatment approach and patient's comorbidities
AI-POWERED CLINICAL DATA PROCESSING FOR:
- HEALTH AUTHORITIES
Quality of medical care improvement and costs reduction✜ Risk assessment for identification of patients not achieving treatment goalsConnect eMed Support
✜ AI prediction of indicators missing in the EHR and selection of patients with prognostic deviations in LDL-C, EF and GFR
✜ Management of high-risk chronic CV patients through treatment strategy recommendation for optimal treatment achievement - PUBLIC AND PRIVATE CLINICS
+30% additional consultations and tests for treatment target achievement✜ Automatization of EHRs analysis for tracking of chronic patients' treatment goals achievement and optimal routing to GP or cardiologistTest eMed Support
✜ Enhancement of heart health check-ups with digital cardiovascular assessment
✜ Reduction of GP's time for 120+ patient characteristics assessment to 1 min vs 40 min, enabling high-quality communication with patient
✜ Accurate medicine procurement planning taking into account evidence-based treatment approach and patient's comorbidities
New Self-Supervised Multivariate Clinical Model (SSMCM)
built for digital twins generation, prediction and prevention of cardiovascular events
built for digital twins generation, prediction and prevention of cardiovascular events
Join us
EMed Support Systems FZ LLC
in5 Tech, Al Sufouh 2
Dubai, UAE
EMED SUPPORT SYSTEMS LTD
Georgiou A 13, STALA COURT Flat/Office 3, Germasogeia 4040, Limassol, Cyprus
in5 Tech, Al Sufouh 2
Dubai, UAE
EMED SUPPORT SYSTEMS LTD
Georgiou A 13, STALA COURT Flat/Office 3, Germasogeia 4040, Limassol, Cyprus
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