Manual evaluation of tissue sections using a microscope is a very time-consuming process. The adoption of AI solutions which can automatically recognize and count visual information could help increase the speed and accuracy of image analysis, whilst also freeing up time for pathologists. Technology Networks recently spoke with Dr Gillian Beamer, a pathologist and assistant professor at Tufts University and Thomas Westerling-Bui, Director, Scientific Strategy and Business Development at Aiforia, to learn how the implementation of a cloud-based platform is helping to advance scientific research on Mycobacterium tuberculosis. Anna MacDonald (AM): Can you provide an overview of what your typical daily work involves? What were some of the challenges you faced doing this manually?

Pathology, the study and diagnosis of disease, is a growth industry. As the global population ages and diseases such as cancer become more prevalent, demand for keen-eyed pathologists who can analyze medical images is on the rise. In the U.K. alone, about 300,000 tests are carried out daily by pathologists. In the U.S., there are only 5.7 pathologists for every 100,000 people. By 2030, this number is expected to drop to 3.7.