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fc function » _ function (Expand Search), a function (Expand Search), 1 function (Expand Search)
within function » fibrin function (Expand Search), python function (Expand Search), protein function (Expand Search)
algorithm rate » algorithm based (Expand Search), algorithm a (Expand Search), algorithm ai (Expand Search)
rate function » brain function (Expand Search), a function (Expand Search), gene function (Expand Search)
algorithm fc » algorithm etc (Expand Search), algorithm pca (Expand Search), algorithms mc (Expand Search)
fc function » _ function (Expand Search), a function (Expand Search), 1 function (Expand Search)
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Multimodal reference functions.
Published 2025“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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The convergence curves of the test functions.
Published 2025“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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Single-peaked reference functions.
Published 2025“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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Test results of multimodal benchmark functions.
Published 2025“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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Fixed-dimensional multimodal reference functions.
Published 2025“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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Test results of multimodal benchmark functions.
Published 2025“…Utilizing the diabetes dataset from 130 U.S. hospitals, the LGWO-BP algorithm achieved a precision rate of 0.97, a sensitivity of 1.00, a correct classification rate of 0.99, a harmonic mean of precision and recall (F1-score) of 0.98, and an area under the ROC curve (AUC) of 1.00. …”
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Wav2DDK: An automated DDK estimation algorithm (Kadambi et al., 2023)
Published 2023“…Estimated rates achieve a high test-retest reliability (<em>r</em> = .95) and show good correlation with the revised ALS functional rating scale speech subscore (<em>r </em>= .67).…”