The startup develops a healthcare technology that employs artificial intelligence to aggregate, analyze, and visualize dispersed medical data for enhanced patient monitoring. This solution enables continuous access to critical health information, ensuring timely medical oversight for patients.
Funding
$5M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
ICU environments face challenges related to specialist shortages, uneven distribution of medical resources, and increased workloads for healthcare professionals, especially given the rising number of critically ill elderly patients. Traditional ICU setups may not be scalable or accessible enough to provide consistent, high-quality care across all hospital beds.
Solution
CROSS SYNC offers an AI-powered remote patient monitoring system designed to extend ICU-level care to any hospital bed. Their 生体看視 (Seitaikanshi) application aggregates and analyzes real-time patient data to provide early warnings and facilitate rapid information sharing among medical staff. By integrating ICT and AI with medical expertise, the system aims to enhance diagnostic accuracy, accelerate treatment, and simplify complex monitoring tasks, ultimately optimizing resource allocation and improving patient outcomes.
Target Audience
The primary target audience includes hospitals, intensive care units, and healthcare providers seeking to improve patient monitoring, optimize resource utilization, and extend ICU-level care to a broader patient population.
Features
- Real-time patient status monitoring and visualization
- AI-driven analysis for accurate severity assessment
- Secure information sharing and communication tools for healthcare teams
- Customizable dashboards and alerts for proactive intervention
- Integration with existing hospital systems and data sources
- Remote access capabilities for continuous monitoring from any location
- Predictive analytics to anticipate patient deterioration and optimize care plans