Hospital Acquired Conditions News and Resources for Healthcare

Epic Risk Model Moderately Successful at Predicting Acute Kidney Injury

March 4, 2024 - Researchers from Mass General Brigham Digital demonstrated that the commercially available, machine learning-based Epic Risk of hospital-acquired acute kidney injury (HA-AKI) model is moderately successful at predicting the condition, according to a study published recently in NEJM AI. The Epic Risk of HA-AKI model works by combing inpatient...

Machine Learning Model Estimates Optimal Treatment Timing for Sepsis

April 10, 2023 by Shania Kennedy

Researchers from Ohio State University (OSU) have developed a machine learning (ML) model that can accurately estimate optimal treatment timing for sepsis cases and support clinical decision-making,...

Johns Hopkins Machine-Learning Tools Predict Risk of ICU Delirium

January 27, 2023 by Shania Kennedy

Johns Hopkins University researchers have developed machine-learning (ML) algorithms that can detect the early warning signs of delirium and predict which patients will be at high risk of delirium at...

Geisinger Chosen as Finalist in CMS Artificial Intelligence Challenge

November 19, 2020 by Jessica Kent

CMS has selected Geisinger as one of seven finalists in its Artificial Intelligence Health Outcomes Challenge. In collaboration with Medial EarlySign, the health system used artificial intelligence...

Risk Scores Predict Patients Likely to Develop Multiple Infections

May 04, 2020 by Jessica Kent

Certain risk scores already used to evaluate the severity of a trauma patient’s condition can also help providers determine which patients are highly likely to develop multiple infections,...

Geisinger Advances in CMS Artificial Intelligence Challenge

November 20, 2019 by Jessica Kent

CMS has selected Geisinger and EarlySign, a machine learning company, for their joint proposal in the agency’s Artificial Intelligence Health Outcomes Challenge. The partnering organizations are...