AI at the edge is transforming patient care, harnessing medical data instantly to give patients greater control of their health, and enabling medical professionals everywhere to deliver personalized care. Learn more about breakthroughs at the intelligent edge.
A new way is needed
The reality is, many healthcare organizations are struggling to run AI workloads at scale due to data management issues, the increasing connectivity of the Internet of Things (IoT) devices, and legacy technology, which limit the true benefit of AI insights.
Instead of transmitting sensitive information over slow WAN connections back to a centralized data center, edge computing eliminates the consumption of bandwidth, latency, and connectivity issues and saves medical organizations valuable time and resources. To drive progress in areas as diverse as patient engagement, diagnostics, and drug and therapy development, caregivers, staff, and researchers need to be able to rapidly collect, analyze, and make decisions based on troves of medical data is essential
Because nowhere is data exploding more
By 2025, the compound annual growth rate (CAGR) for medical data will reach 36%. Insights streaming from the IoT are adding to this mountain of data. The data generated by connected medical devices, wearable health monitors, and other sources is highly sensitive and complex and must be managed effectively to unlock its wealth of information for saving and improving lives. For healthcare facilities, this means delivering insights that allow caregivers to provide patients with timely, effective care. For scientists and researchers, it means speeding up the development of tailored drugs and therapies. Around 60% of adults in the U.S. suffer from at least one chronic condition. Among those aged 65 or older, 85% have one chronic illness.
To make full use of this data for supporting longer, healthier lives, facility managers and IT must work together to ensure their infrastructure can take in, manage, and share all of the medical and research data generated by connected devices and smart equipment at the edge. By expanding the use of AI, this combination of disciplines gives facilities more control over end-to-end operations and enables innovative new healthcare applications. Now, researchers can access information seamlessly from many sources for advancing clinical trials to drug development. It also allows caregivers to monitor patients remotely through health wearables, which speeds up and even automates the delivery of medicine through IoT devices in facilities and our homes.
Checking up on AI at the edge
Virtually no area of healthcare or life sciences will be untouched by this next phase in AI innovation.
Lowering costs with wearable devices and telemedicine
The rise of connected health devices, such as wearables, makes it faster and simpler than ever to monitor and respond to patient needs. With millions of wearable health monitors in use, you can apply insights from devices across a range of environments—including our homes, ambulances, hospitals, operating rooms, and research centers. By delivering medical information when and where it is needed most, patients can gain greater control of their health and empower medical professionals to deliver safe, effective care.
Add to this the benefits of telemedicine. Nearly 75% of all doctor, urgent care, and ER visits could be handled effectively by telemedicine. The intelligent edge will make it possible to treat patients where they live, increasing the availability of care while drastically lowering costs. Wearable devices, such as electrocardiogram monitors and blood pressure monitors, collect and analyze data locally, which a patient can share with their doctor for an instant health evaluation. Using edge sensors to monitor patients in their homes can alert caregivers to changes in a patient's condition and allow them to modify treatments as needed. Telehealth services, remote patient monitoring, and drone delivery of lab samples and medical supplies are just some of the possibilities for AI at the edge.
During the ambulance ride
Very soon, ambulances will become mobile edge computing platforms that will help save even more lives. By equipping emergency vehicles to rapidly process data, emergency medical technicians can gather insights from health monitoring devices and collaborate with doctors on how to stabilize patients, while ER personnel can prepare to handle their specific care needs. This ability is crucial to share vital health knowledge in real time.
Arriving at the hospital
When patients arrive at the hospital, edge computing and AI enable more accurate diagnoses and automate the delivery of medicine. Instead of transporting patients to different rooms and waiting hours for samples and scans to be processed, caregivers can use portable equipment and health monitors to perform testing, capture scans, and check vitals at the patient's bedside. These tools will provide increasingly accurate and up-to-date information for a variety of applications such as automated insulin delivery for patients with diabetes, pre-op and post-op monitoring, and alerting hospital staff to potential safety issues.
Speeding research results
In research and development centers, labs, and in the field, the intelligent edge will also speed up the time between insight and life-saving discoveries. For example, AI at the edge can quickly gather and interpret data from real-world patients to bring new drugs and therapies to market faster. By drawing information from health monitors, ER cases, surgeries, to clinical trials, medical professionals can rapidly share information in order to make more comprehensive and informed decisions. This significantly improves the collaboration between scientists, researchers, and medical staff to improve the quality and delivery of healthcare and help patients enjoy longer, healthier lives.
It’s all happening with AI at the intelligent edge
There's no question that AI at the edge will change what we know about healthcare. But expanding the use of AI is not a black and white task. A broad range of technologies, tools, and applications are essential to accelerate medical insight and drive better results. Healthcare and life sciences organizations need to consider the capabilities required to leverage medical data from diverse locations and millions of connected devices at the intelligent edge.
Empowering the future of medicine at the edge
Healthcare organizations committed to staying at the forefront of edge computing trends will have the ability to disrupt and lead their industries. Using edge-native technologies will help them build modern environments that are expertly engineered for AI:
- Robust edge infrastructure – Designed for extreme performance and resiliency, offering next-generation inference and control capabilities to hospitals, research centers, and everywhere in between
- Edge to data center deployments – Unified infrastructure that orchestrates heterogeneous components to reduce complexity, maximize performance, and increase visibility from edge to exascale
- Automatic prediction and control – Integration of disparate data for real-time and predictive analytics to support faster, smarter decision-making
How HPE and NVIDIA play a leadership role
HPE and NVIDIA are leaders in edge and AI innovation fueling breakthroughs in telehealth and personalized medicine. We are committed to helping organizations successfully deploy AI to harness critical insights from locations around the world. With a wide range of solutions designed to futureproof your edge environments, we unleash medical insights on demand to deliver the most comprehensive view of your patients, create clinical efficiencies, and transform healthcare.
HPE and NVIDIA offer comprehensive solutions and best practices for reinventing healthcare and life sciences organizations. Our robust AI platform is built on HPE systems that are NVIDIA-Certified and enable GPU-accelerated applications for supercharging medical insights to help maximize ROI. The platform combines compute, storage, interconnects, software, and services for a complete solution.
HPE delivers these solutions on-premises, hybrid, or pay-per-use to help simplify system and data management, reduce costs and complexity, and scale to deliver excellent performance. You can choose from an extensive selection of HPE systems that are engineered for AI and powered by NVIDIA GPUs to harness unparalleled processing at any scale.
To optimize workflows for AI model development, deployment, and maintenance for accelerated workflows in healthcare and life sciences, you can leverage the NVIDIA AI Enterprise software suite, which runs on NVIDIA-Certified Systems from HPE. An end-to-end, cloud-native suite of AI and data science tools, NVIDIA AI Enterprise runs on VMware vSphere and includes key enabling technologies and software from NVIDIA for rapid deployment, management, and scaling of AI workloads in the modern hybrid cloud.
It’s time for you to uncover the next breakthrough in patient care. Visit us online to discover how you can succeed at the intelligent edge. Or download the white paper from HPE and NVIDIA: Real-time AI for faster, smarter medical decisions
Katie has held a variety of leadership roles within HPE R&D organizations as well as in Hewlett Packard Labs. She holds an MBA and a BSEE.
Insights Experts
Hewlett Packard Enterprise
twitter.com/HPE_AI
linkedin.com/showcase/hpe-ai/
hpe.com/us/en/solutions/artificial-intelligence.html
TechExperts
Our team of HPE and other technology experts shares insights about relevant topics related to artificial intelligence, data analytics, IoT, and telco.