Smart Dialysis Platform

AI-Driven
Smart Dialysis

Making Every Dialysis Treatment Safer

From assisted to autonomous — through IoT data collection, specialized AI engine, and real-time clinical decision support, we transform dialysis from experience-driven to data-driven.

50+ Centers Deployed | 3000+ Dialysis Machines | Evidence-Based Medicine

The Problem We Solve

Core Clinical Challenges in Traditional Dialysis

Intradialytic hypotension (IDH) occurs in 15-30% of sessions¹, causing myocardial stunning, ischemic brain white matter injury, and other organ damage². Studies show that nadir systolic BP <90 mmHg during dialysis is significantly associated with mortality³, and ultrafiltration rates >10 ml/h/kg increase mortality risk by 9%⁴. Additionally, dry weight assessment is highly experience-dependent, with significant variability between physicians.

Our AI system analyzes BP trends, UF tolerance patterns, and historical treatment data to predict IDH events minutes before onset, optimize UF profiling, and provide evidence-based dry weight recommendations.

References

1. Daugirdas JT. Measuring Intradialytic Hypotension to Improve Quality of Care. J Am Soc Nephrol 2015;26:512-514

2. McIntyre CW. Hemodialysis-Associated Cardiomyopathy: A Newly Defined Disease Entity. Semin Dial 2014;27:87-97

3. Flythe JE, et al. Association of Mortality Risk with Various Definitions of Intradialytic Hypotension. J Am Soc Nephrol 2015;26:724-734

4. Saran R, et al. Longer treatment time and slower ultrafiltration in hemodialysis: associations with reduced mortality in the DOPPS. Kidney Int 2006;69:1222-1228

IDH Prevention

Reduced intradialytic hypotension through predictive alerts

Dry Weight Management

Data-driven dry weight assessment, reducing inter-physician variability

Risk Detection

Multi-dimensional analysis to identify potential complication risks early

Data-Driven Care

Transforming dialysis from experience-driven to data-driven precision management

Core Capabilities

Complete Closed-Loop from Data Source to Clinical Decision

Starting from the data source, we've built a complete chain from data collection, analysis, evaluation, recommendations to real-time feedback.

Dialysis MachinesBP, UF, Blood Flow
Clinical Data LakeLabs, Vitals, Rx
AI AnalyticsIDH, UF, Kt/V
Clinical AlertsReal-time CDSS

IoT Data Infrastructure

Full IoT integration of dialysis machines, BP monitors, scales and core dialysis room equipment. 3,000+ dialysis machines connected with high-frequency data streaming every minute.

3,000+ devices connectedHIS/LIS/EMR integrationStructured clinical data pipeline

Dialysis-Specific AI Engine

Customized LLM trained on dialysis clinical data, combined with AI Agent for IDH prediction, UF rate optimization, and dry weight assessment.

IDH risk predictionUF rate optimizationDry weight trending

Real-Time Clinical Decision Support

Continuous intradialytic monitoring with alerts for BP trends, UF tolerance, access flow, and Kt/V adequacy. Prescription adjustment recommendations integrated into physician workflow.

Intradialytic BP analysisUF & volume managementAdequacy monitoring (Kt/V)
Clinically Proven

Real Data, Real Improvements

60%
Pre-shock patients reduced
22.4% → 9.0%
70%
Lab evaluation efficiency up
8.3 min → 2.5 min
71%
Iron deficiency reduced
74.0% → 21.1%
37%
Renal bone disease reduced
48.4% → 30.7%

Based on data from Suntop-operated dialysis centers, 2024-2025

Validated Deployment Scale

30+
Self-operated Centers
100+
Partner Centers
50+
Smart Dialysis Centers
3000+
Connected Machines