Researchers from the Smidt Heart Institute at Cedars-Sinai, Stanford University, and Columbia University have developed and validated a deep learning (DL) model capable of predicting postoperative...
Researchers have developed and validated a predictive model capable of identifying late postpancreatectomy hemorrhage (PPH) risk in patients with postoperative pancreatic fistula (cr-POPF) following...
A deep learning model can accurately identify non-smokers at high risk for lung cancer using only routine chest X-rays, according to research presented at this year’s meeting of the Radiological...
Researchers at Vanderbilt University Medical Center (VUMC) have developed an artificial intelligence (AI) tool capable of accurately identifying the risk of blood clots in pediatric patients, but found...
A consensus-based, preoperative risk stratification algorithm may help reduce unnecessary oophorectomies in pediatric and adolescent patients with benign ovarian disease, according to a study published...
As medicine advances and healthcare organizations move toward value-based care, providers and health systems are prioritizing population health and preventive care.
But to prevent disease and adverse outcomes for patients, health systems...
In a study recently published in JAMA Network Open, researchers have externally validated a machine learning (ML) model designed to predict six-month mortality risk for patients with advanced cancer...
Effective population health management requires collecting, processing, and analyzing large amounts of patient data, making data analytics tools key for any population health initiative.
Population health is often conceptualized based on...
Researchers have developed a machine learning (ML) model that can accurately predict risk of posttraumatic stress disorder (PTSD) prior to United States military deployment, according to a study...
Researchers at the University of Texas MD Anderson Cancer Center have developed a predictive tool that combines a curated blood test and a personalized risk model to flag those at high risk of...
Researchers from the University of Chicago and Rush University Medical Center have developed a predictive model designed to identify women vulnerable to human immunodeficiency virus (HIV) using EMRs...
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...
A study published recently in Cancer Prevention Research identified seven risk factors for early onset colorectal cancer in males under the age of 50, which researchers posit may improve adherence to...
A study published last week in JAMA Network Open demonstrated that four widely used predictive models for estimating ten-year dementia risk have limited clinical value and utility, indicating that more...
Researchers have shown that omitting race and ethnicity as predictors in colorectal cancer recurrence risk prediction models may be associated with racial and ethnic biases that contribute to health...
Researchers have demonstrated that a machine learning (ML)-based clinical decision support tool can accurately triage patients with respiratory symptoms before they visit a primary care clinic, which...
Computed tomography (CT) scans for coronary artery calcium significantly improved risk predictions for heart disease in middle-aged patients compared to polygenic risk scores, according to a study...
Researchers from Sanford Burnham Prebys and the Chinese University of Hong Kong validated a predictive analytics approach to forecast whether type 2 diabetes patients will develop kidney disease,...
In 2021, preterm births, which occur when an infant is born before 37 weeks gestational age, affected roughly one out of every 10 infants born in the US. The rate of preterm births rose 4 percent in a single year from 10.1 percent in 2020...
Cedars-Sinai researchers have developed an artificial intelligence (AI) tool that can predict a patient’s chance of adverse cardiac events, such as a heart attack, and demonstrate how that...
