More Connected, Personalized, and Intelligent Care

Good technology is designed to let providers focus on the patient and their care. At Intel, our goal is to build technology that enriches the life of every person on earth. Technologies like artificial intelligence (AI), robotics, and the Internet of Things (IoT) are making healthcare and life sciences more connected, personalized, and intelligent.

For example, AI in medical imaging has enabled providers to identify anomalies more quickly and accurately, which can lead to faster diagnoses.1 Other applications of AI in healthcare support customized patient care, surgical precision, intelligent healthcare analytics, and new genomics research. Combined with IoT healthcare technologies, AI has transformed telemedicine, patient monitoring, and electronic health record (EHR) keeping.

Intel healthcare technologies create efficiencies that enable providers to focus more on the human side of care delivery. In lab and research environments, our technology innovations give researchers powerful tools to make breakthrough discoveries and solve some of the world’s largest healthcare and life science challenges. By working together with solution providers and end users in the healthcare community, we’ll continue to develop transformative technologies for the future of healthcare and life sciences.

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Notices and Disclaimers

Intel® technologies may require enabled hardware, software, or service activation.

No product or component can be absolutely secure.

Your costs and results may vary.

Product and Performance Information

1

GE Healthcare medical imaging case study: System test configuration disclosure: Intel® Core™ i5-4590S CPU @ 3.00 GHZ, x86_64, VT-x enabled, 16 GB memory; OS: Linux magic x86_64 GNU/Linux, Ubuntu 16.04 inferencing service docker container. Testing done by GE Healthcare, September 2018. Test compares TensorFlow model total inferencing time of 3.092 seconds to the same model optimized by Intel® Distribution of OpenVINO™ toolkit optimized TF model resulting in a total inferencing time of 0.913 seconds.