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...
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...
A research team from Johns Hopkins Children’s Center has found that an autonomous artificial intelligence (AI) tool to screen youth populations for diabetic eye disease (DED) can also increase...
Researchers from Children’s National Hospital have developed a deep learning (DL) to detect latent rheumatic heart disease (RHD) in children, which may improve case identification and treatment...
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 from Mass General Brigham have found that specialized large language models (LLMs) can identify under-documented social determinants of health (SDOH) in electronic health records (EHRs),...
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...
A research team from the Icahn School of Medicine at Mount Sinai has developed an artificial intelligence (AI) tool to help predict which cardiovascular patients are at increased risk for poor right...
A panel of experts convened by the Agency for Healthcare Research and Quality (AHRQ) and the National Institute on Minority Health and Health Disparities (NIMHD) to address the issue of algorithmic...
De-identified data has become an important tool in medical research and for providers looking to enhance patient care. While data sharing between different organizations could violate the Health...
As health data interoperability becomes an increasingly pressing concern for providers, developers and vendors are paying a great deal more attention to the data standards that will enable seamless,...
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 from Beth Israel Deaconess Medical Center (BIDMC) found that the large language model (LLM) ChatGPT-4 outperforms clinicians in some instances of estimating the probabilities of diagnoses...
A new survey published by the American Medical Association (AMA) shows that clinicians are enthusiastic but cautious about augmented intelligence — also known as artificial intelligence (AI)...
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...
Predictive models using self-report and proxy data can accurately forecast need for nursing home level of care (NHLOC) in community-dwelling older adults with dementia, according to a study published...
A systematic review and meta-analysis of randomized clinical trials (RCTs) published last week in eClinicalMedicine showed that artificial intelligence (AI)-aided colonoscopy may enhance the detection...
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...
