Nature highlights two AIM publications in special report

In a special report about innovations in AI and digital health, Nature highlights two articles from AIM investigators. The first describes a study published in JAMA Network Open in 2019, which describes a deep-learning algorithm trained on more than 85,000 chest x-rays from people enrolled in two large clinical trials that had tracked them for more than 12 years. Our algorithm scored each patient’s risk of dying during this period. The lead AIM investigator, radiologist Michael Lu of Massachusetts General Hospital, says that the algorithm could be a helpful tool for assessing patient health if combined with a physician’s assessment and other data such as genetics. Such AI programs could end up revealing entirely new links between biological features and patient outcomes.

AIM investigators also published a perspective article in Nature Reviews Cancer about Artificial Intelligence in Radiology. This was featured in Nature as it describes how AI algorithms, particularly deep learning, have demonstrated remarkable progress in radiology. Several AI methods have found myriad applications in the medical image analysis field, propelling it forward at a rapid pace. As AI methods excel at automatically recognizing complex patterns in imaging data and providing quantitative, rather than qualitative, assessments of radiographic characteristics.