pinpointIQ – Medical Alley Association

pinpointIQ

NorthShore University HealthSystem, Carnegie Mellon University and PhysIQ Launch Comprehensive Study of New Technology to Monitor At-Risk Cardiac and Surgical Patients

CHICAGO, IL – NorthShore University HealthSystem (NorthShore), Carnegie Mellon University, and physIQ are collaborating on a multi-phase pilot project using the pinpointIQ™ solution to manage patients with heart failure and patients undergoing ileostomy. These patient populations historically have significant clinical risks when transitioning from the hospital to home. Using this solution, NorthShore will be able to continuously monitor at-risk patients […]

UI Health, Chicago Medical Society and PhysIQ Collaborate to Protect Frontline COVID-19 Health Care Workers and High-Risk Patients with Advanced AI

UI Health will monitor the health of certain frontline health care workers and high-risk patients with COVID-19 who are recommended for home isolation using the pinpointIQ system comprising wearable biosensors and artificial intelligence technology The system may help mitigate a surge of hospital patients and provide early warning signs of COVID-19 exacerbation CHICAGO, IL – June […]

PhysIQ Applies Ebola Expertise to Fight COVID-19

PhysIQ uses over one million hours of training set data to implement new machine learning analytics aimed at detecting early signs of COVID-19. This expertise will help mitigate a surge of hospital patients and reduce patient and healthcare provider exposures during the COVID-19 pandemic. This approach allows for increased clinical surveillance of patients being remotely […]

PhysIQ’s Proprietary Personalized Analytics to be Used for COVID-19 Care with Newly Broadened FDA Labeling

PhysIQ announces FDA-sanctioned labeling to address the COVID-19 public health emergency with its proprietary Multivariate Change Index (MCI) Deployed within the pinpointIQ® continuous remote monitoring solution, physIQ’s MCI will be used to proactively monitor homebound patients with or vulnerable to COVID-19 The sophisticated, machine learning-based algorithm uses multiple continuous vital signs from wearable sensors to detect […]

PhysIQ and U.S. Veteran’s Affairs Publish Breakthrough Study Predicting Heart Failure Hospitalization up to 10 days in Advance using AI

PhysIQ and the U.S. VA publish results of a clinical trial that demonstrates how artificial intelligence (AI) applied to continuous wearable sensor data may predict hospitalizations. When coupled with the high sensor wear compliance rates, the 7-10-day early warning timeframe suggests this approach has great promise to reduce hospitalization and improve quality of life of […]

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