Binary encoding scheme. حسب Binh Thanh Dang (12368831)

QSAR model for predicting neuraminidase inhibitors of influenza A viruses (H1N1) based on adaptive grasshopper optimization algorithm حسب Z.Y. Algamal (5547620)

"…Obtaining a reliable QSAR model with few descriptors is an essential procedure in chemometrics. The binary grasshopper optimization algorithm (BGOA) is a new meta-heuristic optimization algorithm, which has been used successfully to perform feature selection. …"

ROC curve for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …"

Confusion matrix for binary classification. حسب Nicodemus Songose Awarayi (18414494)

"…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …"

Example of simulated calcium imaging dataset. حسب Virgil Christian Garcia Castillo (19688355)

"…We observed significant increases in fluorescence activity after formalin injection compared to the control group when using the ROI determination algorithm.…"

Probability density of each bin of accuracy. حسب Virgil Christian Garcia Castillo (19688355)

"…We observed significant increases in fluorescence activity after formalin injection compared to the control group when using the ROI determination algorithm.…"

ROI masks generated when using 2.5 σ1. حسب Virgil Christian Garcia Castillo (19688355)

Datasets and their properties. حسب Olaide N. Oyelade (14047002)

"…However, the underlying deficiency of the single binary optimizer is transferred to the quality of the features selected. …"

Parameter settings. حسب Olaide N. Oyelade (14047002)

"…However, the underlying deficiency of the single binary optimizer is transferred to the quality of the features selected. …"

Identification and quantitation of clinically relevant microbes in patient samples: Comparison of three k-mer based classifiers for speed, accuracy, and sensitivity حسب George S. Watts (7962206)

"…We tested the accuracy, sensitivity, and resource requirements of three top metagenomic taxonomic classifiers that use fast k-mer based algorithms: Centrifuge, CLARK, and KrakenUniq. …"

SHAP bar plot. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

Sample screening flowchart. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

Descriptive statistics for variables. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

SHAP summary plot. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

ROC curves for the test set of four models. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

Display of the web prediction interface. حسب Meng Cao (105914)

"…</p><p>Results</p><p>Logistic regression analysis identified age, hemoglobin concentration, education level, and social participation as significant factors influencing CI. Models based on NNET, RF, LR, and SVM algorithms were developed, achieving AUC of 0.918, 0.889, 0.872, and 0.760, respectively, on the test set. …"

Cotton seed acquisition. حسب Xinwu Du (14626908)

The data processing and analysis pipeline. حسب Xin Zhang (35492)

Flowchart scheme of the ML-based model. حسب Noshaba Qasmi (20405009)

"…<b>I)</b> Testing data consisting of 20% of the entire dataset. <b>J)</b> Optimization of hyperparameter tuning. <b>K)</b> Algorithm selection from all models. …"

Testing results for classifying AD, MCI and NC. حسب Nicodemus Songose Awarayi (18414494)

"…The study introduced a scheme for enhancing images to improve the quality of the datasets. Specifically, an image enhancement algorithm based on histogram equalization and bilateral filtering techniques was deployed to reduce noise and enhance the quality of the images. …"