Researchers from Brigham and Women’s Hospital have determined that a large language model (LLM) may be more accurate at identifying patients with postpartum hemorrhage than standard methods,...
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 from University of California, Los Angeles (UCLA) Health have demonstrated that Generative Pre-trained Transformer 4 (GPT-4) can diagnose and triage various health conditions on par with...
Consolidated, end-to-end data and analytics platforms that allow healthcare organizations to better manage their data and guide business decisions are increasingly important, according to the KLAS Data...
A team of Northwestern Medicine researchers has created a generative artificial intelligence (AI) tool capable of interpreting chest radiographs with accuracy on par with or above radiologists for some...
Artificial intelligence (AI) and deep learning tools may be capable of accurately detecting heart valve disease and predicting the risk of cardiovascular disease events, according to two preliminary...
Researchers have demonstrated that a risk-based lung cancer screening model may reduce racial and ethnic disparities and improve screening efficiency compared to national lung cancer screening...
Researchers at Johns Hopkins Medicine have developed a machine learning (ML) tool capable of estimating the percent necrosis (PN)—the percentage of a tumor that is considered “dead”...
Mount Sinai researchers have demonstrated that publicly trained large language models (LLMs) can identify the pain location and pain location of musculoskeletal conditions like shoulder, knee, and...
Researchers at New York University (NYU) Grossman School of Medicine have demonstrated that a natural language processing (NLP) tool can effectively detect pandemic-related signs of anxiety and...
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...
Researchers at Mount Sinai have developed an artificial intelligence (AI) tool that can estimate histopathological brain age, predict age at death, and identify areas of the brain vulnerable to...
Researchers from the National Institutes of Health Clinical Center (NIH CC) found that a locally run, privacy-preserving large language model (LLM) may be suitable for labeling radiography reports,...
Researchers presenting at the ANESTHESIOLOGY 2023 annual meeting demonstrated that an automated pain recognition system leveraging artificial intelligence (AI) may be capable of detecting pain in...
Researchers from Harvard Medical School (HMS) and the University of Oxford have developed an artificial intelligence (AI) tool capable of predicting how a virus could evolve to escape the immune...
Researchers from the Mount Sinai Icahn School of Medicine and the University of Michigan have found that the deployment of predictive analytics tools may influence the predictive capabilities of...
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...
Researchers at University of Florida (UF) Health have been awarded a $2.8 million grant from the National Institutes of Health (NIH) to develop an artificial intelligence (AI)-based clinical decision...
Researchers from the University of North Carolina (UNC) Department of Surgery, the Joint UNC-North Carolina State University (NCSU) Department of Biomedical Engineering, and the UNC Lineberger...
Researchers at the University of Texas at Arlington (UTA) have been awarded a $450,000 grant from the National Institute of General Medical Sciences to develop a machine learning-based model to predict...
