Medical Data Synthesis Platform
The medical data synthesis platform uses AI to generate virtual datasets that simulate the characteristics of real patient data while protecting patient privacy. It is ideal for medical research, AI model training, and new product development, promoting innovation and data security in healthcare
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Products and Services
Utilizing medical big data and AI technology to generate high-fidelity images, providing high-quality data for the medical and research fields
Data Generator
  • EHR (Electronic Health Record) Synthesis
  • Generate simulated patient health records to assist researchers in conducting large-scale data analysis while protecting privacy
  • Laboratory Data Synthesis
  • Generate various types of laboratory data (such as blood tests and genomic sequencing) to support drug development and disease research
  • Text Data Synthesis
  • Generate text data such as doctor’s notes and diagnostic reports for training natural language processing models and clinical analysis
    Image Generator
  • Pathology Image Synthesis
  • Generate high-resolution pathology tissue slice images to support the development of pathology AI models, such as cancer detection and classification
  • CT/MRI Image Synthesis
  • Generate CT and MRI images of various body parts, covering both normal and pathological states, for imaging model training
  • Ultrasound Image Synthesis
  • Synthesize ultrasound images of different organs to aid in the development of diagnostic tools for conditions such as heart disease and liver disease
    Medical Datasets
  • Customized Patient Features
  • Generate personalized synthetic datasets based on specific patients' health conditions, medical history, and genomic features
  • Multimodal Data Integration
  • Integrate different types of data (such as genomic, imaging, and clinical data) to create a comprehensive patient health record
  • Disease Progression Simulation
  • Simulate the progression of different diseases and treatment responses to assist doctors and researchers in prediction and planning
    Building a Comprehensive Medical Database
    Medical Big Data
    Data Integration and Management
    The intelligent medical data system uses AI and big data technology to automatically integrate and update data, improving quality and retrieval efficiency while ensuring data security and privacy
    Laboratory Testing
    The intelligent laboratory system uses AI and big data to enable automated analysis, rapid reporting, and data integration
    Pathology
    The intelligent pathology system uses AI and big data to automatically identify lesions in pathology, process and integrate data in real-time, and ensure data security while providing accurate predictions
    Imaging
    The intelligent imaging system uses AI and big data to automatically analyze images, process and integrate data in real-time, and provide accurate diagnostics and risk assessments
    Electronic Medical Records (EMR)
    The intelligent medical record system uses AI and big data to enhance the efficiency and accuracy of record management, providing smart decision support and health monitoring
    Different Types of Synthesis
    Fully Synthetic
    Fully synthetic datasets that do not include any real data
    Partially Synthetic
    Variables are replaced with synthetic versions of the data
    Hybrid Synthesis
    Find a similar record in the synthetic data and merge them to create hybrid data
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    The Value of Synthetic Data
    Facilitated research innovation and improved the efficiency of data-driven decision-making
    Privacy Protection
    Synthetic data does not contain personal information, effectively avoiding privacy breaches. It is especially suitable for scenarios requiring data sharing, such as in the medical and financial fields
    Data Augmentation
    In cases of insufficient or hard-to-obtain data, synthetic data can be used to supplement and enrich datasets, thereby improving the performance of machine learning models
    Cost Reduction
    Compared to collecting and annotating real data, generating synthetic data can save a significant amount of time and cost, especially in challenging data generation scenarios
    Testing and Validation
    Synthetic data can be used to test and validate the performance of algorithms under various conditions, helping developers identify and address potential issues in advance
    Our Advantages
    Comprehensively enhance the efficiency and reliability of pathology diagnosis
    Precise Data Synthesis and Diagnostic Support
    PathoGen uses AI and medical big data to create high-quality pathology images and reports. It analyzes patient information, retrieves similar cases, and helps doctors make accurate diagnoses
    Powerful Datasets and Model Validation
    The platform builds and integrates diverse pathology datasets, supporting data training and validation for large models. It enhances model accuracy and applicability, driving advancements in medical research and innovation
    One-Stop Technology Framework
    The platform constructs and integrates diverse pathology datasets, supporting data training and validation for large models. This enhances model accuracy and applicability, driving advancements in medical research and innovation
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    Dedicated Consultant Services
    Customized Products and Solutions
    24/7 Emergency Response
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