AI is expected to have a transformative impact on healthcare, especially radiology. According to a new analysis in the European Journal of Radiology, however, there are significant ethical issues that need to be addressed for any legitimate progress to be made.

For RSNA’s Radiology journal, AI was one of the most popular topics of 2019.

The American College of Radiology (ACR) Data Science Institute (DSI) has created a new resource for radiology researchers: a full list of FDA-cleared AI algorithms related to medical imaging.  

Convolutional neural networks (CNNs) can be trained to detect lung nodules on chest x-rays, according to a new study published in Artificial Intelligence in Medicine.

GE Healthcare has launched a new program designed to make it easier for health systems to implement AI solutions.

The market for blockchain technology in healthcare could exceed $500 million by 2022, according to a new report. This includes an estimated compound annual growth rate of 61.4%.  

Rad AI, a Berkeley, California-based healthcare startup focused on bringing AI to radiology, is launching with a $4 million funding round. The round was led by Gradient Ventures, Google’s venture fund dedicated to AI-related investments.

RSNA 2019 is here and I’m excited to share what’s new from the teams at MEDNAX Radiology Solutions and vRad – especially in the area of AI.