When compared to the performance of 58 dermatologists from 17 different countries around the world, AI missed fewer melanomas and misdiagnosed benign moles less often, according to a study published in the Annals of Oncology.

Convolutional neural networks (CNN) were more accurate than even the most expert dermatologists in detecting skin cancer, researchers reported in Annals of Oncology this week.

Machine learning techniques perform well when tasked with predicting malignancy in breast lesions identified during breast cone-beam CT (CBCT) exams, according to a new study from German researchers published by the American Journal of Roentgenology. One technique, back propagation neural networks (BPN), outperformed two radiologists.

Researchers from the University of Wisconsin-Milwaukee have used a new imaging technique to visualize cellular damage to the retina caused by diabetes. The method, tested in a mouse model, may aid in understanding diabetic retinopathy—a leading cause of blindness.

British Prime Minister Theresa May announced this week she will pledge millions of pounds to the fight against cancer through the development of artificial intelligence (AI), Forbes has reported.

Theresa May, Prime Minister of the United Kingdom, has pledged millions toward government funding that will develop a "new weapon"—artificial intelligence (AI) able to improve cancer and chronic disease diagnosis.

Researchers utilized a machine learning algorithm to determine that a higher rate of change—rather than actual value of cancer antigen 125 (CA125)—is associated with abdominal recurrence of ovarian cancer. Findings may help identify patients most likely to benefit from imaging surveillance of the disease.

University College London Hospitals (UCLH) have partnered with the Alan Turing Institute to use machine learning and artificial intelligence (AI) to complete tasks currently handled by nurses and clinicians, according to The Guardian.