Predictive Analytics

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...


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Deep learning tool may advance precision medicine approaches

by Shania Kennedy

Researchers from Clemson University have developed a deep learning tool to better understand how gene-regulatory network (GRN) interactions impact individual drug response, according to a study...

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Researchers from the University of Pittsburgh Medical Center (UPMC) have developed a predictive model to forecast metastatic uveal melanoma patients’ response to adoptive therapy, according to a...

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by Editorial Staff

As healthcare organizations pursue improved care delivery and increased operational efficiency, digital transformation remains a key strategy to help achieve these goals. Many health systems’...

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A multi-institutional team of researchers has identified an artificial intelligence (AI)-based video biomarker capable of helping clinicians more accurately understand which patients are likely to...

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,...

Computational model uses biomarkers to predict Alzheimer’s progression

by Shania Kennedy

Researchers from Duke University School of Medicine and Pennsylvania State University have demonstrated that a personalized model using individual biomarker data can accurately forecast Alzheimer's...

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,...

NIH funding development of AI tools for health disparity research

by Shania Kennedy

George Washington University (GW) School of Medicine and Health Sciences (SMHS) and the University of Maryland Eastern Shore (UMES) have been awarded a two-year, $839,000 National Institutes of Health...

AI reveals race-based differences in the expression of depression

by Shania Kennedy

Researchers from the University of Pennsylvania, Philadelphia, and the National Institute on Drug Abuse (NIDA) have demonstrated that artificial intelligence (AI) models designed to predict depression...

Machine learning tools predict COVID-19 vaccine hesitancy, uptake

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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...

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MRI-based prostate cancer risk calculators prone to underprediction

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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

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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

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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...

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