The Use of AI in Cancer Screenings

Medical imaging, an integral part of the cancer screening process, continues to experience rapid, year-over-year growth. Unfortunately, available radiologists cannot keep pace with the demand for their services fueled by the continued growth in cancer screening. New solutions are in desperate need to support diagnosis and improve workflows. Can AI play an important role in cancer screenings today and in the future? That’s what Health and Life Sciences at the Edge’s Tyler Kern wants to find out, and Intel’s Business Development and Sales Lead, Ryan Kim, and Lunit’s Director of INSIGHT Marketing, Jonathan Yang, have answers. 

The disparity between the growing need for cancer screenings and the radiologists available to do the work can lead to missed early detection of cancers on chest X-rays and mammograms. Yang says this situation can create a big problem. “Regarding mammography, a high number of screenings can be read as false-positive, meaning that only a single digit percent of those recalled are retested,” he explains. “So, this is where AI can come in.  AI isn’t here to replace radiologists, but it is here to support them, especially regarding cancer screening.” Yang sees many potential benefits AI can provide in assisting cancer screenings for patients, physicians, and medical institutions.

AI-driven solutions can reduce physicians’ reading time.  Yang states, “This allows physicians to spend more time on the hard and tough cases. It also enables early detection of disease.”

Integrating AI into the cancer screening process is a seamless process today. Yang says there are two ways to integrate AI into the diagnostic imaging workflow. The first is when an image is acquired, and the second is during the image interpretation process. In both cases, Luni partners with companies with imaging platforms to make the integration seamless for healthcare institutions.

The utilization of Intel’s OpenVINO™ Toolkit assists in processing images  quickly and minimizing the time from X-ray imaging to diagnosis. With  OpenVINO technology, diagnostics can run on a CPU-only mode of operations, which reduces the cost of operations while delivering on the imaging speed physicians need. 

Learn more about AI-enabled cancer screening solutions by connecting with Ryan Kim and Jonathan Yang on LinkedIn or visit Intel Health and Life Sciences and Lunit’s websites. 

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