WHITEPAPER
How to use disease, real world & population-level data to train AI models
Leveraging robust datasets to improve clinical decision-making and patient outcomes
Turning real world data into actionable AI insights
The intersection of healthcare and AI is revolutionising disease diagnosis, treatment, and management. Success depends on harnessing disease-specific, real world, and population-level datasets to train models that deliver accurate predictions and drive better patient outcomes.
Download the Whitepaper to:
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Understand key data types including EHRs, patient registries, and demographic datasets
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Learn best practices for preprocessing, standardising, and engineering health data for AI training
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Discover AI model training approaches and validation techniques for healthcare applications
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Explore real-world case studies showcasing AI’s role in drug discovery and clinical research