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