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Promoting Health for All with Artificial Intelligence
Technology can enrich the life of every person, especially when it has the potential to help prevent, treat, and cure disease. Intel is working with leaders in the ecosystem to revolutionize health and life sciences, whether it’s accelerating drug discovery to speed pharmaceutical development or improving healthcare access and affordability. The use of artificial intelligence (AI) in healthcare—including computer vision, machine learning, and deep learning—plays a critical role in this goal. Combined with a strong infrastructure for data management, AI can help researchers and health systems quickly gather insights from massive amounts of data that were previously inaccessible due to data silos.
Use Cases for AI in Healthcare and Life Sciences
Artificial intelligence in medicine, pharmaceutical research, and other areas of healthcare can help improve patient care as well as overall population health.2 Today, deep learning and machine learning in healthcare are streamlining workloads for clinicians, informing personalized treatment plans, and enhancing patient experiences.
AI in Medical Imaging
From reducing the compute time needed to generate images from CT scans to performing real-time inference on endoscopic cameras, AI is streamlining workflows and enhancing care.
Precision Medicine
With precision medicine, clinicians use genomic analytics alongside other patient data to customize care and provide the right treatment for each individual.
Predictive Analytics
Predictive analytics can help health systems understand trends, anticipate when and where care will be needed, and improve their population health strategies.
Lab Automation
Computer vision and other types of AI are enabling both speed and accuracy in lab automation.3 Patients can receive their diagnoses fast and new drugs can be tested quickly, leading to breakthroughs in pharmaceutical development.
AI-Enabled Robotics
In hospitals and care facilities, robots are assisting with surgery, streamlining supply delivery and disinfection, and helping providers give more direct attention to patients.
AI in Telemedicine
AI-enabled telemedicine can help clinicians provide timely care and improve outpatient monitoring. Examples include personalized reminders, condition checks based on monitoring data, and dynamic prompts during virtual visits.
Samsung Collaborates with Intel to Speed Nerve Detection and Improve Workflows
Samsung Medison has collaborated with Intel to speed nerve detection and improve workflows. NerveTrack uses the Intel® Distribution of OpenVINO™ toolkit to help detect and identify nerves during ultrasounds. The real-time inference of ultrasound nerve images is helping improve accuracy for anesthesiologists when searching for hard-to-find nerves.
GE Healthcare Accelerates MRI Imaging with AI
GE Healthcare’s Artificial Intelligence Prescription (AIRx) automates some of the manual steps involved in MRI scanning. It also provides a consistent scan alignment to help physicians monitor a patient over several months. Using software optimizations, including the Intel® Distribution of OpenVINO™ toolkit, GE Healthcare reduced the inference time of AIRx from 2.85 seconds to 0.659 seconds on an Intel® Xeon® processor-based platform without the additional cost of accelerators.4
Philips Healthcare Accelerates Algorithms for Magnetic Resonance Imaging (MRI)
Philips Healthcare uses the Intel® Distribution of OpenVINO™ toolkit and the Intel DevCloud for the Edge to speed compressed sensing workloads for their MRI scanners on Intel® Xeon® Scalable Processors with the custom extensions feature of the toolkit.
TGen Applies High Performance Computing to Genetic Research
The next phase of personalized medicine will rely on AI to increase the speed and efficiency of genomic analytics. The Translational Genomics Research Institute (TGen) built a high performance computing (HPC) cluster optimized for life sciences and powered by Intel® Xeon® Scalable processors and Intel® Optane™ memory.
GE Healthcare Helps Staff Triage Life-Threatening Cases
GE Healthcare embedded an AI algorithm on X-ray imaging devices to help flag critical cases and alert radiologists for immediate triage. The Intel® Distribution of OpenVINO™ toolkit improved algorithm performance, speeding the time to analyze an X-ray from more than three seconds to less than one second.1, 5
Akara Prototypes AI-Powered Disinfection Robot
As a proof of concept, Akara developed an autonomous virus-killing robot prototype to disinfect contaminated surfaces in hospitals using UV light. The robot is powered by an Intel® Movidius™ Myriad™ X VPU to navigate around people. Akara’s goal is to help hospitals sanitize rooms and equipment, aiding in the fight against COVID-19.
Develop and Deploy AI Systems
Find documentation and real-world examples of how healthcare systems and researchers have adopted and integrated AI into their workflows.
Accelerating Innovation in the AI Ecosystem
Intel® AI: In Production
AI at the edge enables real-time use cases in healthcare and life sciences. Learn about how Intel’s partners and solutions for health and life sciences are making it possible through Intel® IoT RFP Ready Kits and Intel® IoT Market Ready Solutions.
Intel® AI Builders
Intel® AI Builders brings together independent software vendors (ISVs), system integrators, original equipment manufacturers (OEMs), and enterprise end users. Members gain access to technical enablement resources and comarketing opportunities to help drive edge-to-cloud AI adoption.
Intel® IoT RFP Ready Kits
These RFP-ready bundles of hardware, software, and support help make it possible to develop innovative solutions in healthcare and life sciences. They have been tested in the field and are designed to grow with customer needs.
Intel® Select Solutions for AI
These workload-optimized solution configurations can be deployed in a range of healthcare and life sciences use cases, including genomics analytics.
Intel® IoT Market Ready Solutions
Made possible by Intel’s partner ecosystem, these end-to-end IoT solutions are optimized for data-intensive workloads. Solutions are adaptable, vetted, and ready for implementation.
Find AI Solutions for Healthcare and Life Sciences
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Notices and Disclaimers
Software and workloads used in performance tests may have been optimized for performance only on Intel® microprocessors.
Performance tests, such as SYSmark and MobileMark, are measured using specific computer systems, components, software, operations, and functions. Any change to any of those factors may cause the results to vary. You should consult other information and performance tests to assist you in fully evaluating your contemplated purchases, including the performance of that product when combined with other products. For more complete information visit www.intel.com/benchmarks.
Performance results are based on testing as of dates shown in configurations and may not reflect all publicly available updates. See backup for configuration details. No product or component can be absolutely secure.
Intel® technologies may require enabled hardware, software, or service activation.
Intel does not control or audit third-party data. You should consult other sources to evaluate accuracy. Your costs and results may vary.
Product and Performance Information
“The potential for artificial intelligence in healthcare,” June 2019, Future Healthcare Journal, ncbi.nlm.nih.gov/pmc/articles/PMC6616181/.
“Advantages and limitations of total laboratory automation: a personal overview,” Clinical Chemistry and Laboratory Medicine (CCLM), February 2019, degruyter.com/view/journals/cclm/57/6/article-p802.xml.