Performance of machine learning algorithms. by Wenxue Liu (6877754)

Types of machine learning algorithms. by Md. Merajul Islam (12646837)

“…Thus, the objectives of this study are to develop an appropriate model for predicting the risk of undernutrition and identify its influencing predictors among under-five children in Bangladesh using explainable machine learning algorithms.…”

Algorithmic experimental parameter design. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

ML algorithms in cyber security. by Abdullah Asım Yılmaz (20715311)

Supporting data for “Developing algorithms to optimize recommender system for self-regulated learning promotion in online contexts: a design-based study” by Long Zhang (11129139)

Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

Federated averaging algorithm. by Yan Qin (118276)

DMTD algorithm. by Yunhu Huang (21402795)

Subjects:

Spatial spectrum estimation for three algorithms. by Chuanxi Xing (20141665)

“…Furthermore, the estimation of the DOA can be accurately carried out under low signal-to-noise ratio conditions. This method effectively utilizes the degrees of freedom provided by the virtual array, reducing noise interference, and exhibiting better performance in terms of positioning accuracy and algorithm stability.…”

Performance comparison of mainstream algorithms. by Junjie Lu (160350)

Subjects:

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. …”

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. …”

Data Sheet 1_Development and validation of an endoscopic diagnostic model for sessile serrated lesions based on machine learning algorithms.docx by Xinying Yu (16400811)

“…Background and aims<p>Sessile serrated lesions (SSLs) are morphologically subtle and often misclassified as hyperplastic polyps (HPs), increasing colorectal cancer risks. We developed a machine learning (ML) model to improve endoscopic SSL diagnosis.…”

Table 1_Prediction of myopia onset and shift in premyopic school-aged children: a machine learning-based algorithm.docx by Mingjun Gao (4588822)

“…Purpose<p>This study aimed to investigate longitudinal changes in ocular parameters and develop a machine learning-based model for predicting myopia onset and shift within 1 year in school-aged premyopic children.…”

Data_Sheet_1_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.CSV by Jie Shen (31533)

“…</p>Methods<p>Eligible patients with HCC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and then prognostic models were built using Cox regression, machine learning (ML), and deep learning (DL) algorithms. The model’s performance was evaluated using C-index, receiver operating characteristic curve, Brier score and decision curve analysis, respectively, and the best model was interpreted using SHapley additive explanations (SHAP) interpretability technique.…”

Data_Sheet_2_Development of prognostic models for advanced multiple hepatocellular carcinoma based on Cox regression, deep learning and machine learning algorithms.docx by Jie Shen (31533)

“…</p>Methods<p>Eligible patients with HCC were obtained from the Surveillance, Epidemiology, and End Results (SEER) database, and then prognostic models were built using Cox regression, machine learning (ML), and deep learning (DL) algorithms. The model’s performance was evaluated using C-index, receiver operating characteristic curve, Brier score and decision curve analysis, respectively, and the best model was interpreted using SHapley additive explanations (SHAP) interpretability technique.…”