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derived optimization » required optimization (Expand Search), design optimization (Expand Search), guided optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
dietary data » history data (Expand Search)
its derived » ipsc derived (Expand Search), i derived (Expand Search), hipsc derived (Expand Search)
binary its » binary pairs (Expand Search)
derived optimization » required optimization (Expand Search), design optimization (Expand Search), guided optimization (Expand Search)
driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
dietary data » history data (Expand Search)
its derived » ipsc derived (Expand Search), i derived (Expand Search), hipsc derived (Expand Search)
binary its » binary pairs (Expand Search)
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Flow diagram of the proposed model.
Published 2025“…<div><p>Machine learning models are increasingly applied to assisted reproductive technologies (ART), yet most studies rely on conventional algorithms with limited optimization. This proof-of-concept study investigates whether a hybrid Logistic Regression–Artificial Bee Colony (LR–ABC) framework can enhance predictive performance in in vitro fertilization (IVF) outcomes while producing interpretable, hypothesis-driven associations with nutritional and pharmaceutical supplement use. …”
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Supplementary Material for: Penalized Logistic Regression Analysis for Genetic Association Studies of Binary Phenotypes
Published 2022“…We consider two approximate approaches to maximizing the marginal likelihood: (i) a Monte Carlo EM algorithm (MCEM) and (ii) a Laplace approximation (LA) to each integral, followed by derivative-free optimization of the approximation. …”