Predictive Analytics

Machine learning tools predict COVID-19 vaccine hesitancy, uptake

March 27, 2024 - 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 aversion judgments, according to a study published last week in the Journal of Medical Internet Research (JMIR) Public Health and Surveillance. The...


More Articles

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...

MRI-based prostate cancer risk calculators prone to underprediction

by Shania Kennedy

New research published in JAMA Network Open shows that magnetic resonance imaging (MRI)-based risk calculators can predict prostate cancer risk among adults in Europe and North America with some...

Predictive tool use has little effect on knee surgery decision-making

by Shania Kennedy

Researchers demonstrated that the use of a tool to predict total knee arthroplasty (TKA) in patients with knee osteoarthritis had little impact on patient-reported willingness to undergo the procedure,...

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...

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...

4 Emerging Strategies to Advance Big Data Analytics in Healthcare

by Editorial Staff

While the potential for big data analytics in healthcare has been a hot topic in recent years, the possible risks of using these tools have received just as much attention. Big data analytics...

Epic Sepsis Model Predictions May Have Limited Clinical Utility

by Shania Kennedy

Researchers from the University of Michigan have demonstrated that the Epic Sepsis Model’s risk stratification accuracy was significantly impacted by whether its predictions were restricted to...

Deep Learning Model Accurately Detects, Predicts Alzheimer’s Disease

by Shania Kennedy

A research team from West Virginia University (WVU) has developed a deep learning model capable of detecting and predicting Alzheimer's disease using metabolic biomarkers. The researchers sought...

$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)...

Machine Learning Identifies Drug Candidates for Cardiac Fibrosis

by Shania Kennedy

University of Virginia (UVA) researchers have developed a machine learning tool to identify factors associated with cardiac fibrosis and predict which drug candidates can help prevent the...

What Are the Benefits of Predictive Analytics in Healthcare?

by Editorial Staff

Predictive analytics in healthcare plays a major role in improving care delivery and patient outcomes. By leveraging historical data, this type of analytics allows health systems to gauge what’s...

Machine Learning Tool Predicts Heart Failure Treatment Response

by Shania Kennedy

A research team from The Texas Heart Institute recently developed a machine learning (ML) tool capable of characterizing and predicting diuretic responsiveness in individuals with acute decompensated...

Predictive Model Accurately Tracks Alzheimer’s Disease Progression

by Shania Kennedy

Researchers from the University of Texas at Arlington (UTA) have developed a model to predict how a patient’s Alzheimer's will progress over time, according to a study published recently in...

UC San Diego Risk Stratification AI Predicts Sepsis, Reduces Mortality

by Shania Kennedy

Researchers from the University of California (UC) San Diego School of Medicine have found that an artificial intelligence (AI) model deployed in emergency departments to forecast patients’...

Artificial Intelligence Models May Enhance Immunotherapy Treatments

by Shania Kennedy

Researchers from Cleveland Clinic and IBM have found that artificial intelligence (AI) models can help provide insights into how antigen peptides interact with immune cells, which could be used to...