Image 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png حسب Feng Han (10919)

"…Accurate early risk stratification is essential to guide timely intervention.</p>Objective<p>To develop and validate an interpretable machine learning model for early prediction of severe outcomes following hymenopteran stings.…"

Supplementary file 1_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.docx حسب Feng Han (10919)

"…Accurate early risk stratification is essential to guide timely intervention.</p>Objective<p>To develop and validate an interpretable machine learning model for early prediction of severe outcomes following hymenopteran stings.…"

Image 2_Machine learning enables early risk stratification of hymenopteran stings: evidence from a tropical multicenter cohort.png حسب Feng Han (10919)

"…Accurate early risk stratification is essential to guide timely intervention.</p>Objective<p>To develop and validate an interpretable machine learning model for early prediction of severe outcomes following hymenopteran stings.…"

Image 4_A nomogram-based radiomics for predicting survival to concurrent chemoradiotherapy in inoperable pancreatic cancer: a dual-center cohort study.tif حسب Xin Liu (43569)

"…Firstly, radiomic features were pre-screened by univariate Cox regression and subsequently used to develop 101 machine-learning–based imaging models. An optimized selection algorithm was applied to these models to derive each patient’s radiomic signature (Rad-score). …"

Polyanion sodium cathode materials dataset حسب Martin Hoffmann Petersen (13626778)

"…<p dir="ltr">We have created a polyanion sodium cathode materials dataset that includes optimizations of structures to the lowest energy, ab initio molecular dynamics simulations trajectories sampled at 1000K, and structures generated from ML-driven molecular dynamics simulation at 1000K using active learning algorithms. …"

Data Sheet 1_Risk factor screening and predictive modeling of time-in-range in patients with T2DM undergoing SIIT therapy.docx حسب Yujia Liu (318262)

"…Prediction models were constructed separately using logistic regression and random forest algorithms. Additionally, a nomogram was developed for facilitating clinical application.…"

Table 1_Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.docx حسب Shangshu Zhang (21097439)

"…Feature screening was performed using least absolute shrinkage and selection operator (LASSO) and the Boruta algorithm. Subsequently eight ML algorithms were applied to analyze and identify the optimal model using a 5-fold cross-validation methodology. …"

Table 2_Constructing a screening model to identify patients at high risk of hospital-acquired influenza on admission to hospital.docx حسب Shangshu Zhang (21097439)

"…Feature screening was performed using least absolute shrinkage and selection operator (LASSO) and the Boruta algorithm. Subsequently eight ML algorithms were applied to analyze and identify the optimal model using a 5-fold cross-validation methodology. …"

Image 1_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.tiff حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Image 3_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.tiff حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Table 2_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.docx حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Image 2_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.pdf حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Table 3_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.docx حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Table 1_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.docx حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Image 4_DLML-PC: an automated deep learning and metric learning approach for precise soybean pod classification and counting in intact plants.tiff حسب Yixin Guo (3923948)

"…After 200 epochs, the recognition results of various object detection algorithms were compared to obtain the optimal model. …"

Data Sheet 1_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf حسب Hailong Pang (12841991)

"…The predictive model was constructed using the XGBoost algorithm combined with Shapley Additive exPlanations (SHAP) for interpretability. …"

Data Sheet 1_Interpretable multiparametric MRI radiomics-based machine learning model for preoperative differentiation between benign and malignant prostate masses: a diagnostic, m... حسب Wenjun Zhou (310993)

"…Objective<p>The study aimed to develop and externally validate multiparametric MRI (mpMRI) radiomics-based interpretable machine learning (ML) model for preoperative differentiating between benign and malignant prostate masses.…"

Data Sheet 1_Radiomics-based prediction of recurrent acute pancreatitis in individuals with metabolic syndrome using T2WI magnetic resonance imaging data.csv حسب Yuan Wang (14955)

"…Objective<p>This study sought to clarify the utility of T2-weighted imaging (T2WI)-based radiomics to predict the recurrence of acute pancreatitis (AP) in subjects with metabolic syndrome (MetS).…"

Data Sheet 3_Integrated liquid biopsy model for predicting metastasis and guiding PD-1 therapy in esophageal squamous cell carcinoma.pdf حسب Hailong Pang (12841991)

"…The predictive model was constructed using the XGBoost algorithm combined with Shapley Additive exPlanations (SHAP) for interpretability. …"

Data Sheet 1_Predicting immunotherapy response in stage III-IV non-small cell lung cancer using integrated radiomics and clinical features.docx حسب Na Geng (1927648)

"…Radiomic features were extracted from contrast-enhanced chest CT images, and LASSO algorithm along with Pearson correlation coefficients were applied to select optimal features and calculate a radiomics score. …"