Can AI Reinvent Radiation Therapy for Cancer Patients?

John Halamka, M.D., president, Mayo Clinic Platform, and Paul Cerrato, senior research analyst and communications specialist, Mayo Clinic Platform, wrote this article.Of all the advances in health care artificial intelligence (AI), medical imaging is probably the most remarkable success story. Two prominent examples come to mind: Machine learning has helped improve the screening and diagnosis of retinal disease and is making inroads in skin cancer detection. Given these developments, it ’s not surprising to find researchers and clinicians developing the digital tools to improve radiotherapy, which combines imaging technology with high doses of ionizing radiation, delivered through a device called a linear accelerator.Radiotherapy is one of the most common cancer treatments, used to treat more than half of cancers, yet this labor-intensive expertise is in short supply.1 The digital tools can meet unmet patient needs for the treatment and increase the accuracy of the delivered therapy.  To fully appreciate the impact that AI-enhanced algorithms have on radiotherapy, it helps first to understand how the equipment and technology used to deliver radiation to a patient ’s tumor functions. Ionizing radiation achieves its purpose by disrupting cellular DNA, which prevents cancer cells from growing and dividing, which in turn causes solid tumors to shrink in size. Unfortunately, the same radiation that disrupts tumor growth can also have a detrimental effect on nea ...
Source: Life as a Healthcare CIO - Category: Information Technology Source Type: blogs