Next-Gen AI-Enabled Medical Devices: Tackling Real-Time Analytics Challenges with Advanced Edge Computing

For medical device and AI companies, the core technical challenge currently hindering the development of next-generation products is how to implement real-time, diverse AI functionalities in operational devices.

Taking endoscopy + AI devices as an example, real-time performance is a critical metric for evaluating their capabilities. These devices must process extremely demanding high-definition video streams and perform AI inference computations within a very short timeframe. This imposes exceptionally stringent requirements on the stability and robustness of the device’s computing platform.

In addition to medical imaging equipment, a wide range of devices—including surgical robots—urgently require comprehensive enhancement of their edge AI capabilities in the development of next-generation products.

December 6, 2022, 20:00–21:30,VCBeat SelectJoining HandsNVIDIA, jointly host an online live open class. This course will“Next-Generation AI+Device Products: How to Leverage Powerful Edge Computing to Address the Challenges of Real-Time Analysis?”Focusing on how AI-enabled medical device products, supported by edge computing capabilities, solve real-time analysis challenges through practical case studies.

This session also invitesLiu Jingjia, Co-founder and CEO of Wision A.I.andYuan Yangyan, Senior Product Director at Sinowei Medical Technology Co., Ltd., participate together“AI + Medical Devices/Robotics: What Are the Directions for Next-Generation Products and the Technical Challenges Faced?”Roundtable Discussion: Helping enterprises understand the technical challenges they will face in the R&D of next-generation products and providing solutions.

Viewers who participate in the live interactive Q&A session will also have the chance to receive one of 30 $90 learning vouchers for the NVIDIA Deep Learning Institute (DLI), provided by NVIDIA. DLI offers hands-on training in application development for AI, accelerated computing, and accelerated data science, along with a globally recognized developer certification. This benefit is exclusively available to those who register for the live stream.Scan the QR code in the poster below to register for the live stream:

1. Next-Generation AI + Medical Device Products: Information Processing Capabilities and Real-Time Performance Are Now Essential. What Are the Technical Challenges, and Where Do Application Opportunities Lie?

2. Real-Time AI Applications in Medical Devices: What Are the Challenges in Device Development and AI Application R&D?

3. How Should Technical Architecture and Application Development Evolve in the Face of Challenges?

Founder/General Manager of Medical Device Companies/Robotics Companies/AI Application Developers

[Recommendation: ★★★★★]

Head of R&D/Product Department at Medical Device Companies/Robotics Companies/AI Application Developers

[Recommendation: ★★★★★]

If you belong to the above-mentioned groups or have products that urgently need conversion, be sure not to miss this information-packed open course.

NVIDIADirector of Healthcare Applications, China, responsible for the deployment of NVIDIA’s technology platform in China’s healthcare and medical industry. Prior to joining NVIDIA, he worked on the research, development, and implementation of AI algorithms and applications at companies and institutions including Tencent, GE Healthcare, Toshiba Medical, and Samsung Research. Dr. Yongnan Ji earned his Ph.D. in Computer Science from the University of Nottingham, UK. He is an expert in medical imaging and artificial intelligence applications, with dozens of academic papers and core patents to his name, spanning interdisciplinary fields such as medical imaging and AI-driven image analysis.

Holds a Ph.D. in Optical Engineering from Tsinghua University. Primarily engaged in the research and development of optical and imaging-related medical devices. Currently serves as Senior Product Director at SinoMicro Medical Technology Co., Ltd., overseeing product R&D for the surgical visualization platform portfolio, including 3D endoscopes, 4K endoscopes, fluorescence endoscopes, image processors, surgical robot imaging systems, and observation systems.

Co-founder and CEO of Wision A.I. Holds a Master’s degree in Management Science from Stanford University and a Bachelor’s degree from Beijing University of Posts and Telecommunications. Prior to founding Wision A.I., he worked at multinational technology companies including Cisco, Google, and Amazon AWS, holding roles in technology, marketing, and management. He is well-versed in the cycles, methodologies, and practices involved in the commercialization and market penetration of innovative technology products.

NVIDIAIt is an AI computing company specializing in creating innovative products for computers, consumer electronics, and mobile endpoints that have the potential to transform entire industries. Accelerated computing and AI are powerfully empowering next-generation medical devices and biomedical research. NVIDIA Clara™ supports innovation in the healthcare industry and accelerates the development of precision medicine through a platform for medical imaging, genomics, and patient monitoring that can be deployed anywhere—from embedded systems to the edge, and to every cloud.

“Artery Open Course” is one of the brand columns under VCBeat’s “VCBeat Select.” Focusing on pain points in the medical field and discussions of systematic solutions, it leverages an online live-streaming platform for knowledge sharing and exchange. By continuously inviting seasoned industry practitioners and experts to collaboratively develop a series of thematic courses, it aims to provide medical enterprises with in-depth, high-value practical content. Artery Open Course: Making the selection of knowledge simpler.

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