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...
A research team from the University of Illinois Urbana-Champaign’s Beckman Institute for Advanced Science and Technology has developed a deep learning-based medical imaging approach designed to...
Big data analytics is a major undertaking for the healthcare industry.
Providers who have barely come to grips with putting data into their electronic health records (EHRs) are now tasked with...
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 the University of Pittsburgh (Pitt) and UPMC have developed a smartphone application that leverages artificial intelligence (AI) to diagnose ear infections, specifically acute otitis...
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...
The American Heart Association (AHA) released a scientific statement in Circulation this week detailing the current state of artificial intelligence (AI) use in the diagnosis and treatment of...
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...
A report published this week by the American Medical Association (AMA) and Manatt Health outlines the transformational potential and associated risks of augmented intelligence, also known as artificial...
Researchers from Pennsylvania State University (PSU) have developed a natural language processing (NLP) framework to improve the efficiency and reliability of artificial intelligence (AI)-driven...
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...
Researchers from the New York Eye and Ear Infirmary of Mount Sinai (NYEE) demonstrated that OpenAI’s Generative Pre-Training–Model 4 (GPT-4) can match, or in some cases outperform,...
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 Stanford University and the University of Washington have developed an auditing framework designed to shed light on the ‘black box’ decision-making processes of healthcare...
Artificial intelligence (AI) chatbots like ChatGPT, Google Bard, and BingAI provide information about musculoskeletal health with inconsistent accuracy, according to recent studies presented at the...
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)...
Cedars-Sinai researchers have developed an artificial intelligence (AI)-driven virtual reality (VR) tool to provide mental health support for patients with mild to moderate anxiety or depression,...
The American Health Information Management Association (AHIMA) has launched its AI Resource Hub to provide healthcare and health information (HI) stakeholders with knowledge around the use of...
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...
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...