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Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation
We propose a novel molecular fingerprint-based variational autoencoder applied for molecular generation on real-world drug molecules.
Semantic Decomposition Improves Learning of Large Language Models on EHR Data
Electronic health records (EHR) are widely believed to hold a profusion of actionable insights, encrypted in an irregular, semi-structured format, amidst a loud noise background.
Phenotype Detection in Real World Data via Online MixEHR Algorithm
Understanding patterns of diagnoses, medications, procedures, and laboratory tests from electronic health records (EHRs) and health insurer claims is important for understanding disease risk and for efficient clinical development, which often require rules-based curation in collaboration with clinicians.
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