Explore more about: Biomedical Informatics

One day, the ultrasound equipment that health care professionals use for essential diagnostic imaging may no longer be confined to the clinic, instead operated by patients in the comfort of their homes. New research marks a major step toward that future.

Researchers have found that AI models could accurately predict self-reported race in several types of medical images, suggesting that race information could be unknowingly incorporated into image analysis models.

Minority patient groups may receive less supplemental oxygen in the ICU due to inaccurate readings from pulse oximeters.

NIBIB-funded engineers are using deep learning to differentiate tumor more accurately from normal tissue in positron emission tomography (PET) images.

A team of engineers has demonstrated how a new algorithm they developed was able to successfully predict whether or not a COVID-19 patient would need ICU intervention. This artificial intelligence-based approach could be a valuable tool in determining a proper course of treatment for individual patients.

A new article looks at the use of virtual imaging trials in effective assessment and optimization of CT and radiography acquisitions and analysis tools to help manage the coronavirus disease (COVID-19) pandemic.