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...
A research team from the University of Texas at Arlington (UTA) has developed an algorithm to provide optimal personalized treatment options for esophageal cancer patients, according to a January study...
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...
In a recent viewpoint published in the Journal of the American Medical Association (JAMA), researchers from the University of California San Diego (UCSD) argued that the White House Executive Order on...
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...
Clinical decision support tools can help organizations manage large volumes of data while enabling them to deliver quality, value-based care.
Designed to sort through large amounts of data and provide...
Insights from Deloitte’s 2024 Health Care Generative AI Outlook Survey indicate that healthcare executives’ narrow focus on data could create blind spots that could prevent organizations...
Researchers from Johns Hopkins University and Columbia University have developed a technique to improve the performance of artificial intelligence (AI) and machine learning (ML) models for medical note...
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...
The World Health Organization (WHO) has released new guidance on the governance of large multi-modal models (LMMs) – a type of generative artificial intelligence (AI) – in healthcare.
The...
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...
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...
The question of how the healthcare industry can leverage artificial intelligence (AI) ethically and responsibly has become a hot topic in recent years.
Throughout 2022 and 2023, industry professionals, policymakers, and regulatory...
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),...
