Data Sheet 1_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.docx by Rui Zhang (13940)

“…The model for potential pregnancy loss was also developed using five machine learning algorithms and was based on 7 indicators. …”

Performance of models by different algorithms. by Yong Zhang (5893)

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Control Parameters of IRSA Algorithm. by Wan-Hua Zhang (21601139)

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Image 2_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

“…</p>Method<p>In this study, a robust and accurate prediction model for osteoporosis was developed and validated based on machine learning and SHAP techniques. …”

Table 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.docx by Jiaming Wang (2637667)

“…</p>Method<p>In this study, a robust and accurate prediction model for osteoporosis was developed and validated based on machine learning and SHAP techniques. …”

Image 1_Construction of a clinical prediction model for osteoporosis in asymptomatic elderly population based on machine learning algorithm.tif by Jiaming Wang (2637667)

“…</p>Method<p>In this study, a robust and accurate prediction model for osteoporosis was developed and validated based on machine learning and SHAP techniques. …”

Parameters of ML algorithms. by Md. Maeen Molla (20827041)

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

COMET: A Machine-Learning Framework Integrating Ligand-Based and Target-Based Algorithms for Elucidating Drug Targets by Haojie Wang (3072141)

“…Computational methods can efficiently narrow down the candidate targets for subsequent experimental validation. We have developed a computational target-fishing method, termed COMET, which integrates ligand-based similarity scores with target-based binding scores into a random forest algorithm for target ranking. …”

Data Sheet 1_Development of a novel artificial intelligence algorithm for interpreting fetal heart rate and uterine activity data in cardiotocography.docx by Rohit Pardasani (22253656)

“…The algorithm using deep learning and rule-based techniques was developed to identify segments of interest (accelerations, decelerations, and contractions). …”

Computational Micromechanics and Machine Learning-Informed Design of Composite Carbon Fiber-Based Structural Battery for Multifunctional Performance Prediction by Mohamad A. Raja (19640297)

“…To preform accurate forecasts on energy storage, a data-driven machine learning approach based on artificial neural networks (ANN) was optimized via a Bayesian optimization algorithm to predict the structural battery’s future capacity. …”

Characteristics of training algorithms. by Tuan Anh Nguyen (121944)

“…<div><p>Data training algorithms based on Artificial Intelligence (AI) often encounter overfitting, underfitting, or bias issues. …”

Variables tested in the ML algorithms. by Gilson Yuuji Shimizu (19837946)

“…<div><p>Background</p><p>Studies of cardiovascular disease risk prediction by machine learning algorithms often do not assess their ability to generalize to other populations and few of them include an analysis of the interpretability of individual predictions. …”

Table 1_Predicting liver metastasis in pancreatic neuroendocrine tumors with an interpretable machine learning algorithm: a SEER-based study.docx by Jinzhe Bi (21225545)

“…Furthermore, the SHAP framework revealed that surgery, N-stage, and T-stage are the primary decision factors influencing the machine learning model’s predictions. Finally, based on the GBM algorithm, we developed an accessible web-based calculator to predict the risk of liver metastasis in PaNETs.…”

Supplementary Material for: An Online Machine Learning Algorithm-Based Prognostic Predictive Model for Maintenance Hemodialysis Patients by figshare admin karger (2628495)

“…Six types of machine learning algorithms based predictive models were constructed for prognostic prediction. …”

DataSheet1_Development of a COVID-19 early risk assessment system based on multiple machine learning algorithms and routine blood tests: a real-world study.docx by Qiangqiang Qin (12533191)

“…</p>Methods<p>In this retrospective study, we divided a portion of the data into training and validation cohorts in a 7:3 ratio and established a model based on a combination of two ML algorithms first. …”

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

Predicting CO₂ Solubility in Diverse Ionic Liquids: A Data-Driven Approach Using Machine Learning Algorithms by Zahra Bastami (21474755)

Example measurement and analysis units for landscape elements. by Jaewon Han (8660295)

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