CORDIS Project
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This project aims to enhance molecular diagnostics by developing foundation models that utilize vast biomolecular data. By employing self-supervised learning, it seeks to improve predictions related to cancer subtypes and patient prognosis without relying on extensive labeled datasets.
Molecular diagnostics is crucial in fulfilling the promise of personalized medicine.
While we are amidst an AI revolution, current machine learning models (ML) struggle to effectively learn from molecular (‘omics’) patient profiles and fail to make robust predictions.
Perhaps this is not a surprise.
After all, molecular disease biology is immensely complex, and we ask ML models to predict such complicated things as patient prognosis, without them ‘knowing’ anything about molecular biology and ba…
UNIVERSITAIR MEDISCH CENTRUM UTRECHT
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