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PereDoc采用深度学习为代表的人工智能技术,结合海量医疗数据,研发、医疗影像辅助诊断识别系统,以领先国际的云计算, 大数据和人工智能技术,打造数字化、移动化、智能化的辅助医疗诊断平台

Intelligent Diagnosis Platform Global Resource Linker Intelligent Medical Education Institute Product Introduction PereBox Hardware

PereDoc BOX System Parameters

  • Identification Speed

    Only 20 milliseconds to identify each CT image

  • Daily Detection Volume

    Detect 6 million CT images per day

  • Multiple Users

    Support simultaneous access of 64 users

  • Storage Capability

    Store tens of thousands of medical records and image data

  • Stability

    99.999%

  • Concurrent Operations

    Support 8-route simultaneous detection

  • Detection Speed of Individual Case

    Detection time of each case is less than 2 seconds

  • Floating-point Calculation Capability

    8192GFlops

  • Low Noise

    31 dB, ultra-quiet

  • Volume

    225×203×128mm

  • Power

    2*19.5V/180W power adapter

  • Data Exchange Standard

    HL7 (Healthcare Level 7) Health Information Open Data Exchange Standard

    DICOM3.0 Digital Medical Imaging Communication Standard

    IHE Integrated Healthcare Technology Framework

    ASTM Laboratory Information System and Examination Equipment Interface Standard

    EDI(Electronic Data Interchange)

    EDI (Electronic Data Interchange) Transmission Format

    Disease Classification Code ICD-10

    Logical Observation Identifiers Names and Codes (LOINC)

    Systematized Nomenclature of Medicine (SNOMED)

    Basic Information Classification and Codes of Chinese Hospital Information System

  • Image Encryption Algorithm

    Support JPEG image encryption algorithm based on DCT quantitative coefficient recombination

  • Optional Modules

    Thin-section CT screening of pulmonary nodule and aided diagnosis module

  • User Friendly

    Simple application and interface, even doctors with no programming background can master and complete deep learning modeling after training

PereDoc BOX System Parameters

  • Identification Speed

    Only 10 milliseconds to identify each CT image

  • Daily Detection Volume

    Detect 12 million CT images per day

  • Multiple Users

    Support simultaneous access of 128 users

  • Storage Capability

    Store tens of thousands of medical records and image data

  • Stability

    99.999%

  • Concurrent Operations

    Support 8-route simultaneous detection

  • Detection Speed of Individual Case

    Detection time of each case is less than 2 seconds

  • Floating-point Calculation Capability

    16384GFlops

  • Low Noise

    35 dB, ultra-quiet

  • Volume

    656×218×443mm

  • Power

    500W power adapter

  • Data Exchange Standard

    HL7 (Healthcare Level 7) Health Information Open Data Exchange Standard

    DICOM3.0 Digital Medical Imaging Communication Standard

    IHE Integrated Healthcare Technology Framework

    ASTM Laboratory Information System and Examination Equipment Interface Standard

    EDI (Electronic Data Interchange) Transmission Format

    Disease Classification Code ICD-10

    Logical Observation Identifiers Names and Codes (LOINC)

    Systematized Nomenclature of Medicine (SNOMED)

    Basic Information Classification and Codes of Chinese Hospital Information System

  • Image Encryption Algorithm

    Support JPEG image encryption algorithm based on DCT quantitative coefficient recombination

  • Optional Modules

    Thin-section CT screening of pulmonary nodule and aided diagnosis module

  • User Friendly

    Simple application and interface, even doctors with no programming background can master and complete deep learning modeling after training

The world's first AI-based intelligent hardware in therealm of medical technology