Table 1_A comparative analysis of binary and multi-class classification machine learning algorithms to detect current frailty status using the English longitudinal study of ageing... by Charmayne Mary Lee Hughes (12959972)

“…</p>Conclusion<p>Machine learning algorithms show promise for the detection of current frailty status, particularly in binary classification. …”

The illustration depicts our CQ-CNN architecture for binary image classification. by Mominul Islam (3513758)

Presentation_1_Modified GAN Augmentation Algorithms for the MRI-Classification of Myocardial Scar Tissue in Ischemic Cardiomyopathy.PPTX by Umesh C. Sharma (10785063)

“…Currently, there are no optimized deep-learning algorithms for the automated classification of scarred vs. normal myocardium. …”

DataSheet_1_Multi-Parametric MRI-Based Radiomics Models for Predicting Molecular Subtype and Androgen Receptor Expression in Breast Cancer.docx by Yuhong Huang (115702)

“…We applied several feature selection strategies including the least absolute shrinkage and selection operator (LASSO), and recursive feature elimination (RFE), the maximum relevance minimum redundancy (mRMR), Boruta and Pearson correlation analysis, to select the most optimal features. We then built 120 diagnostic models using distinct classification algorithms and feature sets divided by MRI sequences and selection strategies to predict molecular subtype and AR expression of breast cancer in the testing dataset of leave-one-out cross-validation (LOOCV). …”

Figure 5 from Characterization of Non-Monotonic Relationships between Tumor Mutational Burden and Clinical Outcomes by Jordan Anaya (14850896)

Data_Sheet_1_Alzheimer’s Disease Diagnosis and Biomarker Analysis Using Resting-State Functional MRI Functional Brain Network With Multi-Measures Features and Hippocampal Subfield... by Uttam Khatri (12689072)

“…The objective of this research was to employ efficient biomarkers for the diagnostic analysis and classification of AD based on combining structural MRI (sMRI) and resting-state functional MRI (rs-fMRI). …”

Modeling Pregnancy Outcomes Through Sequentially Nested Regression Models by Xuan Bi (3096897)

“…Ovulation, pregnancy, and live birth are three sequentially nested binary outcomes, typically analyzed separately. However, the separate models may lose power in detecting the treatment effects and influential variables for live birth, due to decreased sample sizes and unbalanced event counts. …”

Table_1_Fusion of fruit image processing and deep learning: a study on identification of citrus ripeness based on R-LBP algorithm and YOLO-CIT model.docx by Chenglin Wang (430151)

“…The YOLO-CIT model combined with the R-LBP algorithm has a Precision of 88.13%, a Recall of 93.16%, an F1 score of 90.89, a mAP@0.5 of 85.88%, and 6.1ms of average detection speed for citrus fruit ripeness identification in complex environments. …”

Nonparametric Distribution Regression and Change Point Detection in High-Dimensions by Shivam Kumar (17808571)

“…First, we introduce the Functional Regression Binary Segmentation (FRBS) algorithm for change-point detection in the slope function when predictors are functions and responses are scalars. …”

Table_10_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx by Changho Han (1309563)

Table_5_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx by Changho Han (1309563)

Table_8_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx by Changho Han (1309563)

Table_6_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx by Changho Han (1309563)

Table_7_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx by Changho Han (1309563)

Table_9_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.xlsx by Changho Han (1309563)

Sexual behavioural variables by HIV status. by Kwamena W. C. Sagoe (17334446)

“…The educational level was significantly associated with HBV infections. After binary logistic regression, being female (AOR: 0.18, 95% CI: 0.07–0.45, p<0.001) and having a stay of 5 years or more (AOR: 0.07, 95% CI: 0.01–0.60, p = 0.016), increased the risk of having HIV infection. …”

Characteristics of study participants. by Kwamena W. C. Sagoe (17334446)

“…The educational level was significantly associated with HBV infections. After binary logistic regression, being female (AOR: 0.18, 95% CI: 0.07–0.45, p<0.001) and having a stay of 5 years or more (AOR: 0.07, 95% CI: 0.01–0.60, p = 0.016), increased the risk of having HIV infection. …”

Data_Sheet_1_Artificial Intelligence-Enabled ECG Algorithm for the Prediction of Coronary Artery Calcification.DOCX by Changho Han (1309563)

Fast Signal Region Detection With Application to Whole Genome Association Studies by Wei Zhang (405)

“…The idea is to conduct binary splitting with re-search and arrangement based on a sequence of dynamic critical values to increase detection accuracy and reduce computation. …”

Table_5_Deep Learning on High-Throughput Transcriptomics to Predict Drug-Induced Liver Injury.XLSX by Ting Li (117885)