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

“…To reduce the manual tuning effort on optimal network architecture, a genetic algorithm is investigated to automatically search and configure the network architecture. …”

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

Descriptive statistics of algorithms. by Fizza Shafique (19996292)

“…Model of the brushless DC motor using a sensorless control strategy incorporated metaheuristic algorithms is simulated on MATLAB (Matrix Laboratory)/Simulink. …”

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... by Jari Turkia (17912475)

Q-value of comparison of algorithms with WOA. by Fizza Shafique (19996292)

“…Model of the brushless DC motor using a sensorless control strategy incorporated metaheuristic algorithms is simulated on MATLAB (Matrix Laboratory)/Simulink. …”

p-values of comparison of algorithms with WOA. by Fizza Shafique (19996292)

“…Model of the brushless DC motor using a sensorless control strategy incorporated metaheuristic algorithms is simulated on MATLAB (Matrix Laboratory)/Simulink. …”

Development of a machine learning prognostic model for early prediction of scrub typhus progression at hospital admission based on clinical and laboratory features by Youguang Lu (12526579)

“…Eighteen objective clinical and laboratory features collected at admission were screened using various feature selection algorithms, and used to construct models based on six machine learning algorithms.…”

Community modeling. by Colton J. Lloyd (5484473)

Image 1_Development and validation of a blood biomarker-based model for differentiating stroke etiology in acute large vessel occlusion.tif by Weiwei Gao (51947)

“…Objective<p>Early differentiation of stroke etiology in acute large vessel occlusion stroke (LVOS) is crucial for optimizing endovascular treatment strategies. This study aimed to develop and validate a prediction model for pre-procedural etiological differentiation based on admission laboratory parameters.…”

Overview of PREDICATE developed to create viral biomass reactions and predict host-based antiviral targets using host-virus models. by Nantia Leonidou (14833068)

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

“…Six classic machine learning algorithms were utilized to develop the optimal predictive model through 1000 bootstrap resamplings. …”

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

“…Six classic machine learning algorithms were utilized to develop the optimal predictive model through 1000 bootstrap resamplings. …”

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

“…Six classic machine learning algorithms were utilized to develop the optimal predictive model through 1000 bootstrap resamplings. …”

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

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

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

“…Six classic machine learning algorithms were utilized to develop the optimal predictive model through 1000 bootstrap resamplings. …”

Severe pediatric brucellosis prediction model in Yunnan Province, China, 2015–2024. by Xin Ma (37268)

DataSheet_1_A Promising Preoperative Prediction Model for Microvascular Invasion in Hepatocellular Carcinoma Based on an Extreme Gradient Boosting Algorithm.docx by 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.…”

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

SOM modeling results using characteristic bands. by 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. …”

SOM modeling results using full spectral bands. by 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. …”