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design optimization » bayesian optimization (Expand Search)
acid optimization » based optimization (Expand Search), lead optimization (Expand Search), art optimization (Expand Search)
image design » images designed (Expand Search), simple design (Expand Search), space design (Expand Search)
binary data » primary data (Expand Search), dietary data (Expand Search)
data acid » data acod (Expand Search), data aic (Expand Search)
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The statistical description of the original data set of the patients (<i>n</i> = 162).
Published 2025Subjects: -
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The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
Published 2025Subjects: -
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ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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The comparison of the accuracy score of the benchmark and the proposed models.
Published 2025Subjects: -
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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
Published 2025Subjects: -
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Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
Published 2025Subjects: -
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Solubility Prediction of Different Forms of Pharmaceuticals in Single and Mixed Solvents Using Symmetric Electrolyte Nonrandom Two-Liquid Segment Activity Coefficient Model
Published 2019“…Because of the semipredictive nature of the symmetric eNRTL-SAC model, the segment parameter regression is a critical step for solubility prediction accuracy. A particle swarm optimization algorithm is incorporated to preregress conceptual segment parameters of solutes. …”
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Sample image for illustration.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Quadratic polynomial in 2D image plane.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Comparison analysis of computation time.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Process flow diagram of CBFD.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”
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Precision recall curve.
Published 2024“…Furthermore, the matching score for the test image is 0.975. The computation time for CBFD is 2.8 ms, which is at least 6.7% lower than that of other algorithms. …”