Data Sheet 1_Identifying network state-based Parkinson’s disease subtypes using clustering and support vector machine models.pdf by Benedictor Alexander Nguchu (9984371)

“…</p>Methods<p>Here, we employ K-means and hierarchical clustering algorithms on data from the Parkinson’s Progression Markers Initiative (PPMI) to identify network-specific patterns that describe PD subtypes using the optimal number of brain features. …”

Median runtime in seconds for building imputation models and imputing the training set (the Q1 - Q3 range is presented in the shiny app). by Elena Albu (15181070)

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Partial dependence plots (A – G) and the resulting clustered feature importance (H) for each feature and trained model. by Daniel Walke (21680915)

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Communication-Efficient Distributed Estimation and Inference for Cox’s Model by Pierre Bayle (21567081)

“…<p>Motivated by multi-center biomedical studies that cannot share individual data due to privacy and ownership concerns, we develop communication-efficient iterative distributed algorithms for estimation and inference in the high-dimensional sparse Cox proportional hazards model. …”

Algorithms runtime comparison. by Meilin Zhu (688698)

“…Firstly, from the perspective of data-driven, it crawls the historical data of driving speed through Baidu map big data platform, and uses a BP neural network optimized by genetic algorithm to predict the driving speed of vehicles in different periods. …”

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. …”

The robustness test results of the model. by Xini Fang (20861990)

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Schematic diagram of fusion model based on voting mechanism. by Jingru Dong (14076094)

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Developed energy optimization model with LSC based on OAWDO algorithm. by Hisham Alghamdi (20114096)

“…<p>Developed energy optimization model with LSC based on OAWDO algorithm.…”

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

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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). …”

Scatter diagram of different principal elements. by Jizhong Wang (7441697)

“…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”

Data Sheet 1_Predictive model establishment for forward-head posture disorder in primary-school-aged children based on multiple machine learning algorithms.csv by Hongjun Tao (21448853)

“…The performance of each model was evaluated, and the best-performing model was further interpreted using the Shapley Additive Explanations (SHAP) algorithm.…”

Data Sheet 2_Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.pdf by Hanlin Wang (240998)

“…The study extracted radiomic features from the tumor, whole lung, and erector spinae muscles of the patients and applied 11 machine learning algorithms to construct prediction models. Subsequently, the classification performance of all constructed models was compared to select the optimal prediction model.…”

Data Sheet 1_Study on postoperative survival prediction model for non-small cell lung cancer: application of radiomics technology workflow based on multi-organ imaging features and various machine learning algorithms.pdf by Hanlin Wang (240998)

“…The study extracted radiomic features from the tumor, whole lung, and erector spinae muscles of the patients and applied 11 machine learning algorithms to construct prediction models. Subsequently, the classification performance of all constructed models was compared to select the optimal prediction model.…”

Data Sheet 2_Machine learning algorithm based on combined clinical indicators for the prediction of infertility and pregnancy loss.zip by Rui Zhang (13940)

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

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. …”

ECG lead-based algorithm diagram. by Pauline Guyot (8566470)

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Supplementary file 1_The value of unsupervised machine learning algorithms based on CT and MRI for predicting sarcopenia.doc by 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.…”

Pareto optimal front result of MOCOA. by Hang Zhao (143592)

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