How do you identify cancer nodules from X-rays with superhuman performance?
Imidex had invested heavily in building a robust dataset of X-rays; however, their team struggled to develop a model that would meet FDA standards. Echelon DS built a computer vision lung cancer detection model in two weeks, surpassing FDA standards in two weeks and ultimately leading to 510k FDA approval.
About The Company
IMIDEX is an Artificial Intelligence Diagnostics solution provider for lung cancer detection. The company has developed a software-as-a-medical-device solution that enables health providers to better detect nodules that can lead to lung cancer discovery.
According to the American Cancer Society, lung cancer is the leading cause of cancer death, making up almost 25% of all cancer deaths. Each year, more people die of lung cancer than of colon, breast, and prostate cancers combined, the American Cancer Society says. IMIDEX was founded on the mission that it wanted to save lives using data science, and has the goal of becoming the standard of care for lung cancer.
Situation
To meet U.S. Food and Drug Administration (FDA) approvals to bring IMIDEX’s VisiradTM solution to market, it was required to showcase the sensitivity modeling of its lung cancer nodule detection. The goal was to be able to increase identification of lung cancer nodules well beyond the average of a radiologist’s sensitivity.
IMIDEX had collected thousands of chest x-rays, which were reviewed manually by a clinical team. It needed a data science partner to build a machine learning solution that would accelerate the review of x-rays without compromising the sensitivity of nodule detection.
Solution
Echelon DS’s team developed a convolutional neural network that was able to provide a superior way of identifying nodules that well exceeded the sensitivity goals. The solution enabled IMIDEX to reach its solution review deadline and allowed for an advancement to testing specificity goals.
The Echelon DS solution is now integrated into the existing workflow to ingest x-rays before being passed to IMIDEX’s Clinical Integrity Team. As more images are added to the growing database, the machine learning model will continue to increase the diagnostic accuracy to detect lung nodules.