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1
ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction.
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2
The accuracy score change matrix following model development.
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3
The comparison of the accuracy score of the benchmark and the proposed models.
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4
Top-performing model configuration and performance by algorithm type.
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5
The prediction accuracy of simple versus hybrid models.
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6
Flow diagram of the proposed model.
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7
The statistical description of the original data set of the patients (<i>n</i> = 162).
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8
Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%).
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9
The most effective active substances for subfertility treatment.
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10
Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction.
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11
The list of parameters of the modified data set for machine learning (<i>n</i> = 162).
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12
Flow diagram of the conversion of drugs into active substances.
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13
Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction.
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