The HIMSS Global Health Conference & Exhibition is one of the biggest convention and exhibition in the healthcare industry. HIMSS gathers professionals within the healthcare ecosystem from around the globe to showcase the latest technologies and innovations that are driving the advancements in the industry. Join Premio at booth #1611 to learn how our rugged edge computers provide the critical computing power, data processing, and next-gen data storage technology to bring machine intelligence to healthcare applications and to enable advanced AI powered medical imaging at the edge.
Exhibition Date: March 15-17, 2022
Venue: Orange County Convention Center, Orlando, Florida
Booth #: 1611
Edge Computing For Intelligent Healthcare
The global pandemic is accelerating digital transformation in healthcare industry. During the Covid-19 outbreak, telehealth and remote monitoring become essential tools for doctors to provide continuous care for patients while keeping both patients and healthcare providers safe. In addition, the ubiquitous IoT smart devices and wearable health and fitness trackers are used to track patients’ vitals continuously and remotely. With the rapid growth in the amount of data being generated, a distributed computing infrastructure is needed for faster and more accurate diagnosis.
Edge computing brings data aggregation, processing, and storage closer to the source of data generation. This allows better bandwidth optimization, lower latency, and a better control of data to be transmitted to the Cloud. Edge computing provides real-time data processing for data insights to facilitate faster decisions and actions for intelligent healthcare.
AI Powered Healthcare Applications
AI has transformed many industries including healthcare. The advancement in both hardware acceleration and software algorithms are generating more and more use cases that are driving the adoption of AI in the medical field. From diagnosis and treatment plan to patient engagement, AI applications are used to not only help streamline clinician workflow, but also to improve the quality of patient care.
A key AI application in the healthcare industry is image recognition. Radiologists could leverage deep learning inferencing to identify abnormalities in radiology images for faster and more accurate diagnosis. AI could also be used to help with treatment plans. One of the most common AI applications is precision medicine, which AI is used to personalize the most effective treatment plan based on patients’ genes, environments, and lifestyles.
Deploying AI applications require lots of data and specialized hardware solutions to process and store the data. While GPUs are commonly used to provide the critical hardware acceleration for data processing and analyzing, M.2 accelerators are fast, compact, and power efficient solutions that are designed and engineered specifically to run AI algorithms at the edge.