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Success Stories: Edge AI in Medical

2024-02-15

Edge AI is revolutionizing healthcare by enhancing decision-making, patient data management, and care delivery. It assists with challenges like drug discovery and disease diagnosis. AI-powered imaging, for example, improves diagnostic speed and accuracy, surpassing traditional methods like biopsies in detecting larger areas of concern.

Case 1-Delivers Stability and Zero-Latency Computing to the latest AI-Powered Neurosurgery Robots

A Grand View Research report indicates that the market size for surgical robots will expand at a CAGR of 19.3% between 2022 & 2030.  Indeed, advances in surgical navigation, stereotactic technology, AI, medical imaging, and robotics are enhancing precision surgery. These technologies reduce complications, errors, and operating times; and improve diagnosis and procedure outcomes.

Challenges:

 • Multitasking capability to conduct diverse preoperative and intraoperative tasks that require timely precision 

 • Advanced system reliability and protection to prevent crashes caused by occasional OTA BIOS updates

Solutions: 

EPC-B5587 embedded PC as AI-powered robotic platform

Case 2-AIMB-288E Kit Leverages Compact Design to Accelerate Edge AI Deployment

The continual emergence of new diseases and conditions necessitates medical equipment upgrades aimed at helping medical staff improve diagnosis accuracy. These upgrades should help handle increasing amounts of data in an effort to reduce the possibility of misjudgment and resulting misdiagnosis. Accordingly, the use of GPU acceleration architecture to reinforce the AI analysis capabilities of medical equipment has become increasingly common. 

Challenges:  

 • Space and Noise: High-performance GPUs add height and noise, challenging compact, quiet healthcare setups. 

 • High Costs: Custom GPUs raise equipment costs, limiting market appeal.

Solutions :  AIMB-288E Mini-ITX as ultra-THIN GPU-accelerated platform for compact, mobile medical devices. 

Case 3-Endoscopy Diagnosis and Treatment with AI Implementation

Since prevention is often more effective than treatments, endoscopy technology, which involves minimal incisions and minimal patient discomfort, is expected to drive the global endoscopy device market to reach approximately US$47.7 billion by 2028, with a projected CAGR of 6% by that year. Endoscopy technology enables doctors to perform polypectomy procedures instantly with high-resolution images and real-time displays through camera sensors, thereby reducing the risk of cancer development. 

 Challenges:   

• Human Error: Traditional endoscopy's reliance on visual analysis can lead to missed early diagnoses due to fatigue and inexperience. 

• Bulky Systems: AI-enhanced endoscopy often requires advanced GPUs (PCIe), limiting flexibility in compact settings.

 Solutions :  MIO-5377R 3.5" SBC as a perfect balance of performance and compactness

Case 4-Delivers Excellent Graphics and AI Performance to Ultrasound Devices

Ultrasound machines require extreme processing performance and graphics rendering to enhance diagnostic accuracy, and instantly acquire precise images. Analogously, easily moveable is also required to accommodate changing medical scenarios and trends, especially when treating patients with limited mobility or travel/movement restrictions caused by COVID-19.

 Challenges:   

• Additional hardware/software integration costs yield high development expenses 

• Despite space restrictions, these solutions necessitate highly-reliable to deliver accurate and timely service for healthcare 

• Common thermal modules, being too large for compact devices and too noisy for use in medical environments — are ill fitted to mobile ultrasound solutions

Solutions :  SOM-6883 COM Express Type 6 deliver stable AI performance with native AI and QFCS thermal solution

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