The deep learning (DL) model was also equally as accurate for racial minorities who have proven to be more likely to die from cancer, such as black women, according to a May 7 study published in Radiology.

Deep learning (DL) may be able to help healthcare providers predict how patients will respond to intravenous thrombolysis, according to a new pilot study published in Academic Radiology.

Researchers have developed a deep learning model for detecting and delineating chronic myocardial infarction (MI), sharing their findings in a new study published by Radiology.

“The results of this study demonstrate proof of the concept that DL models may aid in the prediction of thrombolysis outcomes,” wrote authors of an April 30 study published in Academic Radiology.

Researchers have developed a new technique, DeepPET, that uses deep learning to turn PET imaging data into high-quality images at a much faster rate than traditional methods. 

Artificial intelligence-based computer-aided detection (AI-CAD) software can help radiologists detect more cancers when interpreting mammograms, according to a new study published in the Journal of Digital Imaging.

"Our findings suggest that patients with higher prechemotherapy DHEAS levels had lower odds of developing self-perceived cognitive impairment,” wrote authors of a study published in Pharmacotherapy: The Journal of Human Pharmacology and Drug Therapy.

"The global obesity pandemic has not only led to a greater incidence of cardiovascular disease and type 2 diabetes, but has also coincided with a rise in brain diseases, such as accelerated cognitive decline and dementia,” wrote authors of an April 23 study published in Radiology.