MIT: MIMIC Chest X-Ray database to provide researchers access to over 350,000 patient radiographs. “Last week, the MIT Laboratory for Computational Physiology, a part of the Institute for Medical Engineering and Science (IMES) led by Professor Roger Mark, launched a preview of their MIMIC-Chest X-Ray Database (MIMIC-CXR), a repository of more than 350,000 detailed chest X-rays gathered over five years from the Beth Israel Deaconess Medical Center in Boston.” Note this seems to be substantially larger than the NIH chest x-ray data set released in 2017..
EurekAlert: Artificial intelligence can dramatically cut time needed to process abnormal chest X-rays . “New research has found that a novel Artificial Intelligence (AI) system can dramatically reduce the time needed to ensure that abnormal chest X-rays with critical findings will receive an expert radiologist opinion sooner, cutting the average delay from 11 days to less than 3 days. Chest X-rays are routinely performed to diagnose and monitor a wide range of conditions affecting the lungs, heart, bones, and soft tissues.”
Duke University: Doctor Dolls, Coming Soon In 3-D . “If the board game ‘Operation’ had a 3-D action figure, this might be it. It was an ivory model of a pregnant woman, small enough to fit someone’s outstretched hands, complete with movable arms and a hollow torso holding tiny hand-carved organs. On a recent spring morning, Duke Libraries’ Rachel Ingold and Erin Hammeke prepared the 300-plus-year-old sculpture for an X-ray scan.”
NIH: NIH Clinical Center provides one of the largest publicly available chest x-ray datasets to scientific community . “The NIH Clinical Center recently released over 100,000 anonymized chest x-ray images and their corresponding data to the scientific community. The release will allow researchers across the country and around the world to freely access the datasets and increase their ability to teach computers how to detect and diagnose disease. Ultimately, this artificial intelligence mechanism can lead to clinicians making better diagnostic decisions for patients.”