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...
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...
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...
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...
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...
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...
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)...
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...
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...
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...
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...
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’...
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...
A research team from the University of Michigan has developed a machine learning tool capable of accurately predicting death, major bleeding events, and the need for blood transfusion in patients...
The use of a precision medicine tool designed by Cedars-Sinai researchers has led to the development of a blood test that outperforms the only United States Food and Drug Administration (FDA)-approved...
Researchers from the University of California, Los Angeles (UCLA) and the University of California, Irvine (UCI) have developed a repository of surgical outcomes data to help the medical research...
Yale researchers have found that the predictive algorithms used to forecast treatment efficacy and guide personalized medicine efforts have limited effectiveness when generalized to patient cohorts...
Researchers from the University of Massachusetts (UMass) Amherst have received a two-year, $278,118 grant from the National Institutes of Health (NIH) to build deep learning models for the early...
Researchers have developed an individual risk prediction model for multiple myeloma, which could significantly enhance prognosis and treatment, according to a study published this week in the Journal...
Researchers have developed a risk score to predict intensive care unit (ICU) admission and ICU survival among community-dwelling older adults, according to a study published in Health Science...
