Emergency Medicine

AI Voice Assistants Insufficient for Layperson CPR Instructions

September 5, 2023 - Researchers from Mass General Brigham, New York’s Albert Einstein College of Medicine, and Boston Children’s Hospital demonstrated that artificial intelligence (AI) voice assistants frequently provided low-quality layperson cardiopulmonary resuscitation (CPR) instructions in a recent study published in JAMA Network Open. Layperson CPR...

Read More


More Articles

Investigating Use Cases for AI, IT Tools in Emergency Medical Services

by Shania Kennedy

Emergency medical services (EMS) and first response teams play an instrumental role in providing timely, life-saving healthcare. To help make emergency care more efficient and improve patient outcomes, many EMS organizations are evaluating...

ML Model Outperforms Standard Methods for Detecting Heart Attacks

by Shania Kennedy

Researchers at the University of Pittsburgh Medical Center (UPMC) have developed a machine learning (ML) tool capable of using electrocardiogram (ECG) readings to detect and classify heart attacks more...

How NorthShore Uses AI, NLP to Tackle SDOH in the Emergency Department

by Shania Kennedy

Identifying and tackling social determinants of health (SDOH) are crucial aspects of any health equity strategy. But establishing how best to capture patients’ SDOH needs and develop interventions in the clinical setting remains a...

Case Report Demonstrates Potential Utility of AI in AFib Detection

by Shania Kennedy

In a recent case report published in Cureus, researchers discussed the benefits and challenges of artificial intelligence (AI) in healthcare while presenting a case of atrial fibrillation (AFib)...

Cancer Symptom Algorithm Assists Doctors in Foreseeing ED Visits

by Mark Melchionna

A study published in the Journal of the National Comprehensive Cancer Network (JNCCN) described how a cancer symptom algorithm provided insight into which patients may be at high risk for unplanned...

DL Tool Triages Chest Pain Patients, Predicts Adverse Outcomes

by Shania Kennedy

A new study published this week in Radiology shows that a deep-learning (DL) model may help improve care for patients who arrive at the hospital with acute chest pain. According to the news release,...

How a Data-Driven Command Center Can Improve ED Outcomes

by Shania Kennedy

Emergency departments (EDs) serve as an integral front door in hospital systems, supporting numerous patients requiring acute care or inpatient admission on a daily basis. However, healthcare-wide challenges such as capacity management and...

Most Drug Overdose Patients Not Tested for Fentanyl, Synthetic Opioids

by Shania Kennedy

A new study by Epic Research and the University of Maryland’s Center for Substance Abuse Research (CESAR) shows that only 5 percent of drug overdose patients admitted to the emergency department...

ML Models Can Help Optimize COVID-19 Hospital Admission Decisions

by Shania Kennedy

A new study published this month in npj Digital Medicine shows the positive impact of the multisite implementation of a workflow-integrated machine-learning (ML) system to predict short-term risk and...

Machine-Learning Model Helped Streamline 22% of Pediatric ED Visits

by Mark Melchionna

While exploring the possibilities of integrating machine learning into clinical decision-making, a JAMA Network study found that novel machine learning-driven workflows helped improve test ordering...

Artificial Intelligence Can Help Robots Navigate the ED

by Jessica Kent

Researchers at the University of California San Diego have developed an artificial intelligence algorithm that can help robots better navigate the ED. The team has also developed a dataset of...

Predictive Analytics Tool Accurately Assesses Teen Suicide Risk

by Jessica Kent

Using predictive analytics algorithms, a universal screening tool can accurately determine an adolescent’s suicide risk and alert providers of which patients are in need of follow-up...

Machine Learning Tool May Help ED Clinicians Rule Out COVID-19

by Jessica Kent

A machine learning algorithm can detect the likelihood of COVID-19 infection using routine blood tests, potentially lowering the number of patients referred for PCR testing in the ED, according to a...

Predictive Analytics Determines Outcomes in ED Patients with COVID-19

by Jessica Kent

A predictive analytics platform was able to accurately determine the probability of death or need for critical care within seven days for emergency department patients with COVID-19 symptoms, according...

Artificial Intelligence May Accelerate Heart Failure Diagnosis

by Jessica Kent

Artificial intelligence-enhanced electrocardiogram (ECG) may be able to accurately detect heart failure in patients being evaluated in the ER for shortness of breath, according to a study published in...

Artificial Intelligence Can Detect Pneumonia-Causing Bacteria

by Jessica Kent

Artificial intelligence can use information available in the emergency room to predict the kind of bacteria that is causing infection in patients with pneumonia, according to research presented at the...

FDA Leverages Real-World Data to Enhance COVID-19 Response

by Jessica Kent

The Food and Drug Administration (FDA) is leveraging real-world data to better understand COVID-19 risk factors, tailor public health interventions to specific communities, and mitigate the spread of...

Predictive Model Offers COVID-19 Guidelines for Healthcare Workers

by Jessica Kent

Researchers from Stanford University’s department of surgery have developed a predictive model that provides best practice guidelines for operating room team members during the COVID-19 pandemic...

Tool Helps Hospitals Plan for Critical Care Surges During COVID-19

by Jessica Kent

To help hospitals and health systems plan for a surge in critically ill patients during the COVID-19 pandemic, researchers from Rand Corporation have developed an interactive tool that allows...

Recent Articles