Sinkove
Open siteHealth & Wellness
Introduction
Generates synthetic biomedical images for R&D and clinical validation.
Sinkove Product Information
Sinkove – AI-generated Radiology Data is an AI-powered platform that enables researchers to generate synthetic radiology datasets tailored to their needs. It aims to overcome data scarcity, bias, and variability by producing diverse, high-quality imaging data quickly and cost-effectively for AI model training and clinical research.
How it works
- Customise: Tailor the pre-trained AI to your proprietary datasets and requirements.
- Generate: Create digital twins that represent diverse, realistic imaging across disease subtypes.
- Measure: Validate synthetic data for accuracy, reliability, and regulatory compliance.
- Integrate: Seamlessly use AI-generated datasets in your existing research workflows.
Why Sinkove
- Eliminating Data Bias & Improving Diversity: Generate balanced datasets with various patient demographics, disease subtypes, and imaging protocols to improve model performance across populations.
- Accelerating Research Timelines: Produce high-quality imaging datasets in seconds, reducing reliance on slow real-world data collection.
- Standardising Imaging Data Across Protocols: Convert data from different scanners into a unified format for consistent, comparable datasets.
- Reducing High Costs of Patient Recruitment: Use AI-driven virtual patients and synthetic controls to lower recruitment needs and trial costs while maintaining statistical power.
Start Generating Diverse Imaging Datasets
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About
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- Customisable pre-trained AI to fit proprietary datasets
- Generation of digital twins for diverse, realistic imaging across disease subtypes
- Validation tools for accuracy, reliability, and regulatory compliance
- Seamless integration with existing research workflows
- Standardisation of imaging data across different scanners/protocols
- Ability to reduce real-world patient recruitment and trial costs
- Quick generation of diverse synthetic datasets for AI model training