✔ What synthetic data actually is – and what it isn’t

✔ The benefits and challenges of using synthetic data in clinical research

✔ Real-world use cases, from early dementia diagnosis to trial simulation

✔ How digital twins could help predict patient outcomes

✔ Why synthetic data might be especially useful in areas with limited patient access

✔ The regulatory and ethical considerations we’ll need to navigate

🔗 Fraunhofer SCAI - AI in Data Analysis and Simulation (AI-DAS)

🔗 Cynthia Project (IHI)

🔗 PredictOM Project

🔗 IDERHA Project

🔗 CERTAINTY Project (Virtual Twins)

🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician.

🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills.

🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine.

🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities.

🔗 A synthetic data generation framework for Alzheimer's disease

🔗 Generative learning for deep biomarker discovery

🔗 Longitudinal digital twins in Parkinson’s Disease

🔗 Digital twins for clinical research – opportunities and limitations

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