Smart Medical
AMD Xilinx® Alveo™ data center accelerator cards are designed to meet the evolving needs of the modern data center, delivering significant performance improvements over CPUs for critical workloads including machine learning inference, video transcoding, and database search and analysis.
AI Accelerator Card for Medical Imaging Detection
AMD Xilinx® Alveo™ data center accelerator cards are designed to meet the evolving needs of the modern data center, delivering significant performance improvements over CPUs for critical workloads including machine learning inference, video transcoding, and database search and analysis.
- Machine learning finds various applications in medical imaging, spanning across radiology, dermatology, vascular diagnostics, digital pathology, and ophthalmology, where it employs standard image processing techniques.
- In radiology, chest X-rays represent the most prevalent radiographic examination worldwide, with an astonishing number performed annually.
- When faced with the urgency of swift decision-making, human error rates can soar up to 30%. Leveraging machine learning technology to aid in the decision-making process can enhance decision quality, offering supplementary tools for radiologists and other professionals.
Genome Sequencing Solution
By harnessing data center accelerator cards to expedite the optimized GATK algorithm, this solution slashes the computation time for whole genome sequencing (WGS) from several days to under one hour. Additionally, it offers intuitive data analysis software tailored for gene data analysis.
Drastically reduced analysis time Reduce the WGS computation time from few days to within 1hr
Intuitive human interface Use intuitive data analysis software to analyze NGS data without bioinformatics training or additional lab staff.
Reliable accuracy in analysis Achieve the same level or Precision as the champion in precisionFDA Truth Challenge
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With E-Elements leading the way to upgrade your systems
With E-Elements leading the way to upgrade your systems
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