A modular Quantum Sequential Model is proposed and compared against classical regression and symmetry-constrained quantum regressors for predicting hydration status from urinary biomarkers, highlighting opportunities and limitations of near-term quantum computing in digital health.
Water, hydration, and health.Nutrition Reviews, 68(8):439–458, 2010
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Hydration Monitoring Using Urinary Biomarkers: A Hybrid Classical Quantum Predictive Modeling Framework
A modular Quantum Sequential Model is proposed and compared against classical regression and symmetry-constrained quantum regressors for predicting hydration status from urinary biomarkers, highlighting opportunities and limitations of near-term quantum computing in digital health.