PLS-SEM algorithm. حسب Ernest Nyamekye (18451455)

Data Sheet 2_Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outco... حسب Xiaonan Zhang (538829)

"…Using single-cell RNA sequencing and machine learning algorithms, we identified critical TLS-associated genes and developed a TLS-based predictive model. …"

Data Sheet 3_Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outco... حسب Xiaonan Zhang (538829)

"…Using single-cell RNA sequencing and machine learning algorithms, we identified critical TLS-associated genes and developed a TLS-based predictive model. …"

Data Sheet 1_Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outco... حسب Xiaonan Zhang (538829)

"…Using single-cell RNA sequencing and machine learning algorithms, we identified critical TLS-associated genes and developed a TLS-based predictive model. …"

Data Sheet 4_Development of a tertiary lymphoid structure-based prognostic model for breast cancer: integrating single-cell sequencing and machine learning to enhance patient outco... حسب Xiaonan Zhang (538829)

"…Using single-cell RNA sequencing and machine learning algorithms, we identified critical TLS-associated genes and developed a TLS-based predictive model. …"

Risk element category diagram. حسب Yao Hu (3479972)

"…This article used these data to establish an LSTM model, which trained LSTM to identify potential risks and provide early warning by learning patterns and trends in historical data. …"

Data used in "Material Classification System using Inductive Tactile Sensors and Machine Learning Algorithms" حسب Yuning Jiang (19758561)

"…<p dir="ltr">This study presents an innovative material classification system involving an inductive tactile sensor and machine learning algorithms. A simple-structured sensor based on the principle of electromagnetic induction was developed to capture varying inductance signals induced by different materials with distinct magnetic properties, facilitating material detection and distinction. …"

Data from the article titled Machine Learning Algorithms to Predict Digital Competencies in University Faculty حسب Jenniffer Sobeida Moreira Choez (16933539)

"…<p dir="ltr">The data analyzed are part of the study entitled <i>Machine Learning Algorithms to Predict Digital Competencies in University Faculty</i>, which aimed to develop predictive models based on machine learning algorithms to estimate the level of digital competencies among university faculty. …"

Corporate bond coupon prediction based on deep learning حسب Tongyi Liu (92082)

"…Specifically, to optimize the hyperparameters of the proposed model, an improved butterfly optimization algorithm incorporating the concepts of good point sets, refraction opposition-based learning, switching probability adjustment, and Solis & Wets search strategies is developed. …"

Supplementary file 1_The value of unsupervised machine learning algorithms based on CT and MRI for predicting sarcopenia.doc حسب Huayan Zuo (22308277)

"…Objectives<p>This study aims to investigate the efficacy of unsupervised machine learning algorithms, specifically the Gaussian Mixture Model (GMM), K-means clustering, and Otsu automatic threshold partitioning, in predicting sarcopenia based on computed tomography (CT) and magnetic resonance imaging (MRI) data.…"

Explained variance ration of the PCA algorithm. حسب Abeer Aljohani (18497914)

"…These classification algorithms often requires conversion of a medical data to another space in which the original data is reduced to important values or moments. …"

Data Sheet 3_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 2_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 4_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.zip حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 6_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.docx حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Data Sheet 1_A prognostic model for highly aggressive prostate cancer using interpretable machine learning techniques.pdf حسب Cong Peng (160287)

"…Feature selection was performed using the Boruta algorithm, and survival predictions were made using nine machine learning algorithms, including XGBoost, logistic regression (LR), support vector machine (SVM), random forest (RF), k-nearest neighbor (KNN), decision tree (DT), elastic network (Enet), multilayer perceptron (MLP) and lightGBM. …"

Stage 3 Workshops: Investigating the Learning Mechanics - Game Mechanics (LM-GM) model for the development of digital game-based learning حسب Glen Shearer (9834266)

الموضوعات:

Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms حسب Jie Zhu (126574)

"…Six different machine learning algorithms were employed to develop prognostic models based on the clinical features during the acute phase, which were reduced using Lasso regression.…"

Detailed information on software packages used for machine learning model development. حسب Jingru Dong (14076094)

الموضوعات:

Comparative performance evaluation of 3Mont with other feature selection algorithms over 10 iterations. حسب Miray Unlu Yazici (14792680)

الموضوعات: