Machine Learning

Machine learning approach predicts heart failure outcome risk

April 22, 2024 - Researchers from the University of Virginia (UVA) have developed a machine learning tool designed to assess and predict adverse outcome risks for patients with advanced heart failure with reduced ejection fraction (HFrEF), according to a recent study published in the American Heart Journal. The research team indicated that risk models for HFrEF...

Read More


More Articles

Machine learning framework captures uncertainty in medical images

by Shania Kennedy

Researchers from the Massachusetts Institute of Technology (MIT), Massachusetts General Hospital and the Broad Institute of MIT and Harvard have developed a machine learning approach to help capture...

Machine learning characterizes cardiac function, drug response

by Shania Kennedy

Columbia University researchers have developed a machine learning-based approach to assess cardiac function and drug response, according to a study published recently in IEEE Open Journal of...

Machine learning predicts hospitalization during cancer treatment

by Shania Kennedy

Machine learning tools can accurately forecast an unplanned hospitalization event during concurrent chemoradiotherapy (CRT) using patient-generated health data from wearable devices, according to a...

Machine learning predicts risk of suicide in patients initiating care

by Shania Kennedy

Kaiser Permanente researchers have demonstrated that a machine learning-based predictive model can stratify suicide risk among patients scheduled for an intake visit to outpatient mental healthcare,...

Artificial intelligence in healthcare: defining the most common terms

by Editorial Staff

As healthcare organizations collect more and more digital health data, transforming that information to generate actionable insights has become crucial. Artificial intelligence (AI) has the potential to significantly bolster these...

Machine learning approach may help tailor precision medicine treatments

by Shania Kennedy

A research team from Arizona State University has developed a machine learning (ML) model capable of predicting whether a patient’s immune system will recognize pathogens and other foreign cells,...

Machine learning tools predict COVID-19 vaccine hesitancy, uptake

by Shania Kennedy

Researchers from the University of Cincinnati (UC) and Northwestern University have developed machine learning (ML) models that can accurately predict trends in COVID-19 vaccine uptake using reward and...

Machine learning predicts perioperative peripheral artery disease risk

by Shania Kennedy

Machine learning (ML) algorithms can accurately predict one-year major adverse limb event (MALE) or death following endovascular intervention for peripheral artery disease (PAD), according to a study...

Deep learning tool predicts brain metastasis in lung cancer patients

by Shania Kennedy

A research team from Washington University School of Medicine in St. Louis has developed a deep learning (DL)-based approach to help predict which patients with non-small cell lung cancer (NSCLC) are...

Machine learning enables prediction of pediatric urinary condition

by Shania Kennedy

Researchers from Boston Children's Hospital have developed a machine learning model to predict risk of dilating vesicoureteral reflux (VUR) in infants with hydronephrosis – a condition in...

Mount Sinai to develop sleep apnea outcome risk prediction models

by Shania Kennedy

Researchers from Mount Sinai have been awarded a four-year, $3 million grant from the National Heart, Lung, and Blood Institute of the National Institutes of Health (NIH) to develop artificial...

Machine Learning Predicts Cancer Risk in Liver Disease Patients

by Shania Kennedy

A research team from UC Davis Health developed a machine learning (ML) tool to identify which patients are at increased risk of developing hepatocellular carcinoma (HCC), a common type of liver...

Epic Risk Model Moderately Successful at Predicting Acute Kidney Injury

by Shania Kennedy

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...

AHA Issues Statement on the Use of AI in Cardiovascular Care

by Shania Kennedy

The American Heart Association (AHA) released a scientific statement in Circulation this week detailing the current state of artificial intelligence (AI) use in the diagnosis and treatment of...

Machine Learning Models Predict Mortality Among Dementia Patients

by Shania Kennedy

Researchers at the Icahn School of Medicine at Mount Sinai have developed machine learning (ML) models to identify mortality predictors in dementia patients, according to a study published this week in...

AMA Report Outlines Considerations for AI Integration in Healthcare

by Shania Kennedy

A report published this week by the American Medical Association (AMA) and Manatt Health outlines the transformational potential and associated risks of augmented intelligence, also known as artificial...

Auditing Framework Provides Insights into ‘Black Box’ Medical AI

by Shania Kennedy

Researchers from Stanford University and the University of Washington have developed an auditing framework designed to shed light on the ‘black box’ decision-making processes of healthcare...

Health Systems Prioritize Artificial Intelligence Governance, Oversight

by Shania Kennedy

Health systems are increasingly prioritizing the development of artificial intelligence (AI) oversight efforts as they continue to navigate the potential promise and pitfalls of these tools in...

$4M Grant to Fund Development of Sleep Apnea Outcome Prediction Tools

by Shania Kennedy

Researchers from Mount Sinai have been awarded $4.1 million from the National Heart, Lung, and Blood Institute (NHLBI) at the National Institutes of Health (NIH) to develop artificial intelligence (AI)...

Recent Articles