Google researchers have developed an augmented reality microscope (ARM) that takes real-time data from a trained neural network to detect cancer cells and display them in the field of view of the pathologist viewing the image. The prototype is configured to recognize breast and prostate cancer cells and does not require a hospital or laboratory to replace an existing microscope, as existing composite optical microscopes can be retrofitted with digital cameras to feed images to machine learning algorithms and The digitized results are superimposed on the user's simulated view with a customized AR display. The findings were announced at the annual meeting of the American Association for Cancer Research on Monday. The project's technical director, MarTIn Stumpe, and Google brain team product manager Craig Mermel published an article on the Google Research blog: "We believe in development In China, ARM has the potential to have a major impact on global health, especially in the diagnosis of infectious diseases such as tuberculosis and malaria. In addition, even in hospitals that will adopt digital pathology workflows in the near future, ARM can be digitalized. Workflows are combined, and in this workflow, the scanner will still face significant challenges or require rapid turnaround." A study of machine learning methods previously published by the research team showed that the algorithm achieved an 89% score in detecting tumors, while a trained pathologist without a time limit scored 73%. More and more machine learning and AR have proven to be the perfect match for edge technology. Google recently applied these technologies to enable YouTube creators to change the video background in real time without depth sensors. Facebook researchers use these techniques to identify the effects of the body on potential systemic AR effects. However, as these experiences are entertained, they appear pale and weaker than the actual benefits of improving cancer detection. Product name: B85 Ethereum Mining Rig
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Motherboard Model: B85
CPU Model: Celeron 1840 Dual-Core 2.8GHz
Memory Model: DDR3 4G 1600 16 Particles
Hard Disk Model: Solid State 64G/128G Msata
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Chasis Size: 720mm*360mm*185mm
Card Distance: 55mm
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