Table_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.DOCX حسب Shakiru A. Alaka (9302864)

"…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…"

Data_Sheet_1_Functional Outcome Prediction in Ischemic Stroke: A Comparison of Machine Learning Algorithms and Regression Models.PDF حسب Shakiru A. Alaka (9302864)

"…We evaluate the predictive accuracy of machine-learning algorithms for predicting functional outcomes in acute ischemic stroke patients after endovascular treatment.…"

Variations of loss functions versus epoch number. حسب Xueliang Guo (4797057)

The number of inactive nodes as a function of time steps in (a) a random network and (b) a scale-free network. حسب Waseem Al-Aqqad (14123917)

The number of inactive nodes as a function of time steps at higher values of <i>P</i> and <i>α</i> in (a) a random network and (b) a scale-free network. حسب Waseem Al-Aqqad (14123917)

Reconstructing <i>sparse</i>, binary patterns using message passing algorithms and PCA. حسب Sebastian Goldt (14522594)

Low-Rank Covariance Function Estimation for Multidimensional Functional Data حسب Jiayi Wang (294312)

"…We extend multilinear rank structures for (finite-dimensional) tensors to functions, which allow for flexible modeling of both covariance operators and marginal structures. …"

Experimental design of mechanism combinations. حسب Qiong Wu (84327)

"…The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. …"

Flowchart of SGHHO. حسب Qiong Wu (84327)

"…The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. …"

Framework structure of SGHHO-KNN. حسب Qiong Wu (84327)

"…The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. …"

Parameter setting for 10 metaheuristics. حسب Qiong Wu (84327)

"…The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. …"

Descriptions of each attribute. حسب Qiong Wu (84327)

"…The algorithm can achieve the optimal value of the function on 67% of the tested functions and significantly outperforms other competing algorithms. …"

Flowchart of BWEMFO. حسب Jingjing Ma (419752)

"…The scalability of the algorithm is confirmed through benchmark functions. …"

Various MFOs from three mechanisms. حسب Jingjing Ma (419752)

"…The scalability of the algorithm is confirmed through benchmark functions. …"

The flowchart of MFO. حسب Jingjing Ma (419752)

"…The scalability of the algorithm is confirmed through benchmark functions. …"

Parameters. حسب Jingjing Ma (419752)

"…The scalability of the algorithm is confirmed through benchmark functions. …"

Deep Learning-Based Multi-Scale Bubble Detection and Feature Analysis حسب Lichun Bai (6684683)

"…The spatial and channel reconstruction convolution (SCConv) module is integrated in the neck network of the model to reduce feature redundancy in both the channel and spatial dimensions. …"

Table 1_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.xlsx حسب Yuezhou Huang (9998177)

Table 2_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.xlsx حسب Yuezhou Huang (9998177)

Table 3_SRC is a potential target of Arctigenin in treating triple-negative breast cancer: based on machine learning algorithms, molecular modeling and in Vitro test.docx حسب Yuezhou Huang (9998177)