Penn State Health to Pioneer Next-Generation Virtual ICUs with CLEW Medical’s AI Powered Cloud-based Platform
Bringing virtualICU services in-house and offering them to both owned and referral hospitals in the region, to better manage capacity and address provider shortages driven by prolonged pandemic and burnout.
AI-based clinical decision support tools support more proactive care and increased physician productivity
To improve the efficiency of the European healthcare system, the innovative CLEWICU solution identifies patients with an increased likelihood of being diagnosed with respiratory failure or hemodynamic instability, prioritizes workflow and treatment, and optimizes the allocation of critical care resources
The highly experienced healthcare executives will advise CLEW Medical as the company expands its product offering in North America following FDA 510k approval
CLEW Medical Receives FDA Clearance for AI-Based Predictive Analytics Technology to Support Adult ICU Patient Assessment
CLEWICU is the industry’s first-ever cleared device for predicting the likelihood of patient deterioration up to 8 hours in advance based on hemodynamic instability, enabling earlier evaluation and subsequent care plans
CLEW Receives FDA Emergency Use Authorization (EUA) for its Predictive Analytics Platform in Support of COVID-19 Patients
CLEWICU is the only device authorized by the FDA to provide early identification of patients who are likely to experience respiratory failure or hemodynamic instability, both potentially common but significant complications associated with COVID-19
Relyens forges five exclusive technology partnerships to enhance the operational safety of healthcare professionals and local authorities
Prominent healthcare technology pioneer to advise CLEW as the company expands its product offering across the entire continuum of care
Featuring healthcare industry experts, the program will show how critical care units are using AI-Machine Learning to deliver true patient value
CLEW used Google Compute Engine to build a reliable, scalable, cloud-based machine learning platform to develop and train its critical care algorithms.