For example, let's take medical imaging. The over 600 million procedures each year generate 90% of all health care data, and more than 97% of that data goes unused. Intel's Vision Technologies can create AI solutions that will more quickly analyze the information, from thousands of scans, including X-ray, MRI, ultrasound, and more, resulting in even faster results, higher degrees of patient safety, and more accurate diagnosis through machine-assisted intelligence.

Early diagnosis and detection can be life changing. In the case of lung cancer, early detection can increase the five year survival rate from 5% to over 50%.

Siemens Healthineers is one of the leading medtech companies in the world. Our mission is to expand precision medicine, improve patient experience, helping physicians to diagnose patients, and treat patients more effectively.

In this context, Edge AI Inference becomes an integral part of various solutions that are being translated into clinical workflows. And this is the reason why we need better technologies, faster technologies, that would allow real time inference. And the next generation Intel XEON scalable processor is a great example into that direction.

In imaging, for instance, there is a growing workload for a shrinking population of radiologists who can interpret the images that the devices generate. We work together with Intel using AI to make some of the tasks that burden radiologists more easy.

In cardiac EMR, for example, we're processing the slices of the MR scan at a rate of 200 slices per second, which means that one can process today the entire heart cycle in about one second.

Deep Learning Boosts technology helps us introduce new real time applications into the market without the added complexity and burden of having dedicated accelerators in the system.

We've been using the Openvino platform and part of that platform, there is this fascinating library, MKL DNN, which allows the inner optimization of the algorithm.

Collaborating with the Intel experts helped us greatly to improve the performance of such deep running models in the product by some factors in the range of 3 to 10.

The purpose in healthcare is to do what is right for the patient.

I always see technology as bringing new benefits for the patient. Bringing new benefits for the health system to improve the care and to reduce these costs

Camera technology is being deployed ubiquitously, giving computers the ability to see what is happening. When paired with recent innovations in AI technology, the computers are also able to use Deep Learning to understand or infer what they are seeing. The technology is transforming business outcomes across industries, making cities safer, modes of transportation and manufacturing facilities more efficient, driving increased sales and operational efficiencies for retailers, and providing life saving opportunities through early detection in hospitals.

The possibilities of using computer vision to drive business transformation and outcomes are endless. Please reach out to your Intel account representative or visit us at intel.com/iot. We look forward to partnering with you.