With the help of machine learning, researchers were able to train a computer to analyze breast cancer images and classify tumors accurately, according to a study published in NPJ Breast Cancer.

Ezra, a New York City-based artificial intelligence (AI) startup, has secured $4 million in funding for its new direct-to-consumer prostate cancer screening program.

After receiving FDA clearance for AI software that can detect brain bleeds from CT images, MaxQ AI has announced a deal to integrate the software with medical imaging platforms.

MRI may be a better choice than multidetector CT for identifying high-risk colon cancers that have already reached stage II or stage III, are still surgically resectable and are at risk of progressing to stage IV.

The American Cancer Society (ACS) released a new report highlighting the current state of cancer screening and put forth specific areas requiring further attention to fully maximize the potential of screening to combat cancer.

In an interview with AI in Healthcare, JingJia Liu, chief executive officer at Wision AI, discussed the company's new machine-learning algorithm for polyp detection, what’s next and the impact of AI products in the medical industry.

Brightness of the shoulder’s deltoid muscle on ultrasound can identify patients with type 2 diabetes or pre-diabetes with almost 90 percent accuracy, according to a study being presented at the Radiological Society of North America (RSNA)’s 2018 Annual Meeting next week in Chicago.

“The new 2018 Digital Mammography QC Manual will promote uniformity and consistency of QC procedures across the broad spectrum of FDA approved manufacturers,” Eric Berns, PhD, manual author and chair of the ACR Subcommittee on Mammography Quality Assurance, said in a prepared statement.