Data and percentage of optimal performance of the 3 methods. حسب Wenyu Chen (9135516)

Optimal image settings for object detection of Iba1 immunolabelled cells in DAB. حسب Danish M. Anwer (15383441)

Rapid Prediction of Chemical Ecotoxicity Through Genetic Algorithm Optimized Neural Network Models حسب Ping Hou (17213)

"…In this study, artificial neural network models are developed to predict chemical ecotoxicity (HC₅₀) based on experimental data to fill data gaps in a widely used database (USEtox). …"

A schematic view of the step-by-step computational approach in the current study. حسب Hamed Rezaei (11085366)

Personal recommendations of potassium and phosphorous intake () based on cross-validation predictions of nutrition effects, . Other parameters of the figure are similar to in-sampl... حسب Jari Turkia (17912475)

Data Sheet 1_Machine learning-based high-specificity diagnostic model for Talaromyces marneffei infection in febrile patients using routine clinical laboratory data.pdf حسب Yingjun Xiao (17603738)

"…Objective<p>This study developed and validated a machine learning (ML)-based predictive model utilizing febrile patients’ routine clinical laboratory data for the purpose of screening such patients for Talaromyces marneffei infection and to provide reference information for feature selection in the subsequent establishment of a more precise early warning model.…"

Table 3_Machine learning-based high-specificity diagnostic model for Talaromyces marneffei infection in febrile patients using routine clinical laboratory data.xlsx حسب Yingjun Xiao (17603738)

"…Objective<p>This study developed and validated a machine learning (ML)-based predictive model utilizing febrile patients’ routine clinical laboratory data for the purpose of screening such patients for Talaromyces marneffei infection and to provide reference information for feature selection in the subsequent establishment of a more precise early warning model.…"

Table 2_Machine learning-based high-specificity diagnostic model for Talaromyces marneffei infection in febrile patients using routine clinical laboratory data.xlsx حسب Yingjun Xiao (17603738)

"…Objective<p>This study developed and validated a machine learning (ML)-based predictive model utilizing febrile patients’ routine clinical laboratory data for the purpose of screening such patients for Talaromyces marneffei infection and to provide reference information for feature selection in the subsequent establishment of a more precise early warning model.…"

Table 1_Machine learning-based high-specificity diagnostic model for Talaromyces marneffei infection in febrile patients using routine clinical laboratory data.xlsx حسب Yingjun Xiao (17603738)

"…Objective<p>This study developed and validated a machine learning (ML)-based predictive model utilizing febrile patients’ routine clinical laboratory data for the purpose of screening such patients for Talaromyces marneffei infection and to provide reference information for feature selection in the subsequent establishment of a more precise early warning model.…"

DataSheet_1_A Promising Preoperative Prediction Model for Microvascular Invasion in Hepatocellular Carcinoma Based on an Extreme Gradient Boosting Algorithm.docx حسب Weiwei Liu (341566)

"…Furthermore, to facilitate use of the model in clinical settings, we developed a user-friendly online calculator for MVI risk prediction based on the XGBoost model.</p>Conclusions<p>The XGBoost model achieved outstanding performance for non-invasive preoperative prediction of MVI based on big data. …"

Supporting data for “Digital immunochromatography: A bead-based bilateral zigzag flow immuno-assay with adaptive differential noise correction for rapid and precise protein detecti... حسب Zhiting Peng (9722516)

S1 Data set - حسب Ming-Song Zhao (757598)

"…Characteristic bands were selected from each type of spectra by the competitive adaptive reweighted sampling (CARS) algorithm, respectively. Thirdly, SOM prediction models were established based on random forest (RF), support vector regression (SVR), deep neural networks (DNN) and partial least squares regression (PLSR) methods using optimal spectral indexes, denoted here as SI-based models. …"

Description of the dataset. حسب Davide Ferrari (163517)

"…We further assess its performance by comparing it to established ML algorithms using both naturally imbalanced real-world data and data that has been balanced through oversampling techniques. …"

Sample multi-parameter patient data from the MIMIC-III clinical database: This figure demonstrates the complicated, high-resolution time-series data monitored on a single patient o... حسب Medhat A. Tawfeek (22522087)

Schematic overview of the XBSI framework. حسب Rajeev Bopche (20208606)

Comparative performance metrics of ML models. حسب Rajeev Bopche (20208606)

"…The XAI framework significantly outperformed traditional models, particularly with tree-based algorithms, demonstrating superior specificity and sensitivity in BSI prediction. …"

DataSheet_1_Raman Spectroscopic Differentiation of Streptococcus pneumoniae From Other Streptococci Using Laboratory Strains and Clinical Isolates.pdf حسب Marcel Dahms (9160118)

Local alignment regime and symbols.pdf حسب Paul A. Gagniuc (1818325)

Data Sheet 1_Development and application of machine learning models for hematological disease diagnosis using routine laboratory parameters: a user-friendly diagnostic platform.doc... حسب Jingya Liu (13338460)

Location of study area and sampling sizes. حسب Ming-Song Zhao (757598)

"…Characteristic bands were selected from each type of spectra by the competitive adaptive reweighted sampling (CARS) algorithm, respectively. Thirdly, SOM prediction models were established based on random forest (RF), support vector regression (SVR), deep neural networks (DNN) and partial least squares regression (PLSR) methods using optimal spectral indexes, denoted here as SI-based models. …"