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. …”

Data Sheet 1_Detection of litchi fruit maturity states based on unmanned aerial vehicle remote sensing and improved YOLOv8 model.docx by Changjiang Liang (21099887)

Community Detection with Heterogeneous Block Covariance Model by Xiang Li (114679)

Image from video analysis. by Yunlin Li (6049214)

Association between crowding and oral habits. by Kengo Oka (1420585)

“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”

Association between deep bite and oral habits. by Kengo Oka (1420585)

“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”

Breakdown of participants by residential area. by Kengo Oka (1420585)

“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”

Each variable for the dataset. by Kengo Oka (1420585)

“…The dataset was created, and AI-based binary classification models for malocclusion were developed using an automated machine learning platform (DataRobot) to construct three algorithms for determining malocclusion (deep bite, maxillary protrusion, and crowding). …”

Prediction of health disorders in dairy cows monitored with collar based on Binary logistic analysis by Xiaojing Zhou (521545)

“…<div><p>ABSTRACT The objective of this study was to analyze data on physical activity and rumination time monitored via collars at the farm coupled with milk yield recorded by the rotary milking system to predict cows based on several disorders using the binary Logistic regression conducted with R software. …”

Cell classification. by Adam L. Tyson (10892822)

GSE96058 information. by Sepideh Zununi Vahed (9861298)

“…</p><p>Results</p><p>In this study, five main steps were followed for the analysis of mRNA expression data: reading, preprocessing, feature selection, classification, and SHAP algorithm. …”

The performance of classifiers. by Sepideh Zununi Vahed (9861298)

“…</p><p>Results</p><p>In this study, five main steps were followed for the analysis of mRNA expression data: reading, preprocessing, feature selection, classification, and SHAP algorithm. …”

Melanoma Detection by Means of Multiple Instance Learning by Annabella Astorino (11644324)

“…We present an application to melanoma detection of a multiple instance learning (MIL) approach, whose objective, in the binary case, is to discriminate between positive and negative sets of items. …”

Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx by Hyo-jae Lee (11780051)

“…Objective<p>This study was conducted in order to investigate the feasibility of using radiomics analysis (RA) with machine learning algorithms based on breast magnetic resonance (MR) images for discriminating malignant from benign MR-detected additional lesions in patients with primary breast cancer.…”

Table_1_Classification of MR-Detected Additional Lesions in Patients With Breast Cancer Using a Combination of Radiomics Analysis and Machine Learning.docx by Hyo-jae Lee (11780051)

“…Objective<p>This study was conducted in order to investigate the feasibility of using radiomics analysis (RA) with machine learning algorithms based on breast magnetic resonance (MR) images for discriminating malignant from benign MR-detected additional lesions in patients with primary breast cancer.…”

PathOlOgics_RBCs Python Scripts.zip by Ahmed Elsafty (16943883)

“…</p><p><br></p><p dir="ltr">In the fifth measurement technique, the numbers of sharp <b>surface projections/protrusions</b> were calculated by initially applying Canny's edge detection algorithm to generate an edge map of the cell mask image. …”

Data_Sheet_1_Deep learning-based ultrasonographic classification of canine chronic kidney disease.docx by Heejung Yu (17122910)

HPDmobile H5 Image Zone Labels by Soumik Sarkar (2039536)

“…These were automatically generated with the yoloV5 object detection algorithm (https://github.com/ultralytics/yolov5), and a subset was manually verified by a human. …”

HPDmobile H2 Image Zone Labels by Soumik Sarkar (2039536)

“…These were automatically generated with the yoloV5 object detection algorithm (https://github.com/ultralytics/yolov5), and a subset was manually verified by a human. …”

HPDmobile H6 Image Zone Labels by Soumik Sarkar (2039536)

“…These were automatically generated with the yoloV5 object detection algorithm (https://github.com/ultralytics/yolov5), and a subset was manually verified by a human. …”