بدائل البحث:
within functional » without functional (توسيع البحث), obtain functional (توسيع البحث), brain functional (توسيع البحث)
algorithm python » algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm i » algorithm _ (توسيع البحث), algorithm b (توسيع البحث), algorithm a (توسيع البحث)
i function » _ function (توسيع البحث), a function (توسيع البحث), 1 function (توسيع البحث)
within functional » without functional (توسيع البحث), obtain functional (توسيع البحث), brain functional (توسيع البحث)
algorithm python » algorithms within (توسيع البحث), algorithm both (توسيع البحث)
python function » protein function (توسيع البحث)
algorithm i » algorithm _ (توسيع البحث), algorithm b (توسيع البحث), algorithm a (توسيع البحث)
i function » _ function (توسيع البحث), a function (توسيع البحث), 1 function (توسيع البحث)
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Predictive Mixing for Density Functional Theory (and Other Fixed-Point Problems)
منشور في 2021"…Density functional theory calculations use a significant fraction of current supercomputing time. …"
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143
The convergence curves of the test functions.
منشور في 2025"…For the early-stage diabetes dataset, LGWO-BP achieved an accuracy of 0.92, a recall of 0.93, a precision of 0.88, an F1-score of 0.91, and an AUC of 0.95. 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.
منشور في 2025"…For the early-stage diabetes dataset, LGWO-BP achieved an accuracy of 0.92, a recall of 0.93, a precision of 0.88, an F1-score of 0.91, and an AUC of 0.95. 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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Image 4_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regre...
منشور في 2025"…Objective<p>Investigate the correlation between right ventricular function ultrasound indicators and the Venous Excess Ultrasound (VExUS) grading system in patients undergoing invasive mechanical ventilation (IMV), and develop a right ventricular function assessment model using VExUS grading and the Classification and Regression Tree (CART) algorithm.…"
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Image 3_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regre...
منشور في 2025"…Objective<p>Investigate the correlation between right ventricular function ultrasound indicators and the Venous Excess Ultrasound (VExUS) grading system in patients undergoing invasive mechanical ventilation (IMV), and develop a right ventricular function assessment model using VExUS grading and the Classification and Regression Tree (CART) algorithm.…"
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Image 2_Construction of a right ventricular function assessment model in patients undergoing invasive mechanical ventilation based on VExUS grading and the classification and regre...
منشور في 2025"…Objective<p>Investigate the correlation between right ventricular function ultrasound indicators and the Venous Excess Ultrasound (VExUS) grading system in patients undergoing invasive mechanical ventilation (IMV), and develop a right ventricular function assessment model using VExUS grading and the Classification and Regression Tree (CART) algorithm.…"
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A Python Package for the Localization of Protein Modifications in Mass Spectrometry Data
منشور في 2022الموضوعات: -
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Python implementation of the Trajectory Adaptive Multilevel Sampling algorithm for rare events and improvements
منشور في 2021"…<div>This directory contains Python 3 scripts implementing the Trajectory Adaptive Multilevel Sampling algorithm (TAMS), a variant of Adaptive Multilevel Splitting (AMS), for the study of rare events. …"
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