Man and Machine - Imaging Artificial Intelligence

Man and Machine - Imaging Artificial Intelligence

Radiology is a field that generates large amounts of data and can no longer be managed without the help of smart systems. This is especially true when it comes to interpreting medical images. This takes doctors years of training and experience, a few hours of work, and the highest level of concentration, while AI requires only a few seconds to perform the same task.

Big Data needs smart algorithms

According to estimates, the amount of medical data is expected to increase by about 50 percent annually. Most - 90 percent - are produced in medical imaging. In 2019 alone, radiology will produce 675 billion gigabytes of image data. This translates into a staggering 13.5 trillion cross-sectional images - a quantity that's hard to imagine if you can't imagine it. In fact, only 7 percent of these images are processed. The 100th German X-ray Congress held in May discussed these numbers. It is impossible to manually tackle this business, making machine support crucial to meeting the growing demand.

Artificial Intelligence not only operates at consistently high speeds and precision, but also identifies hidden patterns in data and gives doctors valuable support in diagnostic and treatment decisions. Machine learning is particularly useful where diagnostic data are being reviewed and digitized by doctors.