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,...
A study published last month in JAMA Network Open described a new machine learning (ML) tool that may assist clinicians in identifying older adults with advanced cancer who are at higher risk of...
Researchers from the University of Florida have created a predictive analytics tool capable of identifying acute lymphoblastic leukemia (ALL) patients’ risk for complications from chemotherapy...
A study published earlier this month in JAMA Network Open demonstrates that a newly-developed multimodal model using brain function information and other risk factors can improve the prediction of...
The Agency for Healthcare Research and Quality (AHRQ) highlights care management as a fundamental means of managing the health of defined populations and supporting the triple aim of healthcare.
AHRQ and the Center for Health Care...
Researchers have validated a causal artificial intelligence model designed to identify a patient’s inherited risk of coronary artery disease (CAD) and provide personalized recommendations for...
Cerebral aneurysms, also known as intracranial or brain aneurysms, present a unique challenge for clinicians, as most are small dilations that occur at weak points along the arteries of the brain and have no symptoms. However, as the...
In a study published this week in Science Translational Medicine, researchers from the Stanford School of Medicine revealed that a machine-learning (ML) algorithm could predict prematurity...
Corewell Health care coordinators shared that a recent initiative, which uses predictive analytics to forecast risk and reduce readmissions, has kept 200 patients from being readmitted and resulted in...
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...
A study published last week in JAMA Network Open found that a machine learning (ML)-based model leveraging available administrative data can accurately estimate adverse opioid outcomes, which could...
In a recent study, researchers validated a deep-learning (DL) model to predict lung cancer risk using chest radiographs and EMR data.
The Centers for Disease Control and Prevention (CDC) report that...
A study published this week in Scientific Reports comparing hypertension incidence prediction models found little difference in performance between machine-learning (ML) models and conventional...
A mixed-methods quality improvement study published in JAMA Network Open found that using suicide risk estimation analytics did not augment existing prevention practices as intended during routine...
Researchers from the University of California, San Diego (UC San Diego) and New Light Technologies Inc. (NLT) announced a partnership to develop an infectious disease risk platform designed to serve as...
University of California (UC) Davis Health has partnered with artificial intelligence (AI) software company Illuminate to develop a centralized abdominal aortic aneurysm surveillance program aimed at...
In a new study published last week in JAMA Network Open, researchers found that a suite of predictive analytics tools leveraging readily available EHR data can accurately identify all-cause 30-day...
University of California Davis researchers have received a $15 million, five-year grant renewal from the National Cancer Institute (NCI) to fund artificial intelligence (AI) projects aimed at improving...
Researchers at the University of Houston (UH) have developed an artificial intelligence (AI)-based clinical decision support tool that leverages deep learning (DL) to predict which patients are more...
A new study published in JAMA Network Open found that adding continuous intraoperative data to routinely collected perioperative data used by machine learning (ML)-based mortality prediction models...
