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Synthetic Data Algorithm
- Project
- 20050 Secur-e-Health
- Type
- New product
- Description
Implemented an algorithm to create synthetic data, individual patient-level data from aggregated data.
- Contact
- Mika Teikari, Ornela Bardhi
- mika.teikari@successclinic.fi
- Research area(s)
- synthetic data
- Technical features
Transform aggregated healthcare data into individual-level data.
- Integration constraints
• Operating System: Microsoft Windows 10 (Version 10.0.19045, 64-bit) • Processor: AMD Ryzen 7 PRO 3700 • Anaconda 3: specific environment for the synthetic data project • JupyterLab Version 4.0.11 • Python Version: 3.10.11
- Targeted customer(s)
Pharmaceutical companies, Pharmaceutical manufacturing, Government agencies
- Conditions for reuse
Confidential
- Confidentiality
- Confidential
- Publication date
- 31-12-2027
- Involved partners
- SUCCESS CLINIC OY (FIN)