Section Channel classification (Binary classification part): Weights obtained by the optimised classification algorithm. حسب Fabien Raphel (9421987)

Binary classification accuracy comparing each algorithm for predicting “high” risk of mortality in the test cohort (n = 125,657). حسب Stephen F. Weng (3903466)

"…<p>Binary classification accuracy comparing each algorithm for predicting “high” risk of mortality in the test cohort (n = 125,657).…"

Flowchart for classification tasks in automated extinction risk assessment method, using the XGBoost algorithm [29]. حسب Gabriel Henrique de Oliveira Caetano (12647413)

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... حسب Charmayne Mary Lee Hughes (12959972)

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

Evaluation of Binary Classifiers for Asymptotically Dependent and Independent Extremes حسب Juliette Legrand (21771740)

Comparison with previous studies. حسب Ji Seung Ryu (16187857)

"…This retrospective study used electrocardiographs obtained at Yonsei University Wonju Severance Christian Hospital, Wonju, Korea, from October 2010 to February 2020. Binary classification was performed for primary screening for left ventricular hypertrophy. …"

Dataset characteristics. حسب Ji Seung Ryu (16187857)

"…This retrospective study used electrocardiographs obtained at Yonsei University Wonju Severance Christian Hospital, Wonju, Korea, from October 2010 to February 2020. Binary classification was performed for primary screening for left ventricular hypertrophy. …"

Acronym table. حسب Ji Seung Ryu (16187857)

"…This retrospective study used electrocardiographs obtained at Yonsei University Wonju Severance Christian Hospital, Wonju, Korea, from October 2010 to February 2020. Binary classification was performed for primary screening for left ventricular hypertrophy. …"

Random forest model performs better than support vector machine algorithms and when it primarily uses spontaneous photopic ERG of 60-s duration in humans. حسب Ramsés Noguez Imm (6658637)

Reproducing kernel-based semiparametric functional smoothed score estimation with binary responses حسب Meichen Liu (8168148)

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

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

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

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

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

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

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

Fairness in Machine Learning: A Review for Statisticians حسب Xianwen He (22529252)

"…We organize these fairness-enhancing mechanisms into three categories—pre-processing, in-processing, and post-processing—corresponding to different stages of the machine learning lifecycle and varying levels of access to the underlying algorithm. The discussion focuses on fairness in binary classification models using numerical tabular data, which serve as a foundation for addressing fairness in more complex algorithms. …"

Spontaneous ERG-based random forest model discriminates control and disease cases in rodent models of obesity and type 1 diabetes and predicts disease evolution in the type 1 diabe... حسب Ramsés Noguez Imm (6658637)

Multicategory Angle-Based Learning for Estimating Optimal Dynamic Treatment Regimes With Censored Data حسب Fei Xue (24567)

"…Specifically, the proposed method obtains the optimal DTR via integrating estimations of decision rules at multiple stages into a single multicategory classification algorithm without imposing additional constraints, which is also more computationally efficient and robust. …"