Optimized Bayesian regularization-back propagation neural network using data-driven intrusion detection system in Internet of Things by Ashok Kumar K (21441108)

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Flow diagram of the proposed model. by Uğur Ejder (22683228)

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Top-performing model configuration and performance by algorithm type. by Uğur Ejder (22683228)

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Event-driven data flow processing. by Yixian Wen (12201388)

“…Subsequently, we implement an optimal binary tree decision-making algorithm, grounded in dynamic programming, to achieve precise allocation of elastic resources within data streams, significantly bolstering resource utilization. …”

The statistical description of the original data set of the patients (<i>n</i> = 162). by Uğur Ejder (22683228)

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The list of parameters of the modified data set for machine learning (<i>n</i> = 162). by Uğur Ejder (22683228)

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ROC and PR–AUC curves of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

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The accuracy score change matrix following model development. by Uğur Ejder (22683228)

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The comparison of the accuracy score of the benchmark and the proposed models. by Uğur Ejder (22683228)

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The prediction accuracy of simple versus hybrid models. by Uğur Ejder (22683228)

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Comparison of baseline and hybrid machine learning models in predicting IVF outcomes (%). by Uğur Ejder (22683228)

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The most effective active substances for subfertility treatment. by Uğur Ejder (22683228)

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Confusion matrix of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

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Flow diagram of the conversion of drugs into active substances. by Uğur Ejder (22683228)

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Calibration curve of the ABC–LR–RF hybrid model for IVF outcome prediction. by Uğur Ejder (22683228)

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UK Biobank data wrangling statistics and results. by Simeone Marino (81051)

Experimental observation of gastruloids and shape quantification using LOCO-EFA. by Martijn A. de Jong (17896732)

Data_Sheet_1_A Data-Driven Framework for Identifying Intensive Care Unit Admissions Colonized With Multidrug-Resistant Organisms.docx by Çaǧlar Çaǧlayan (12253934)

“…</p>Materials and Methods<p>Leveraging data from electronic healthcare records and a unique MDRO universal screening program, we developed a data-driven modeling framework to predict MRSA, VRE, and CRE colonization upon intensive care unit (ICU) admission, and identified the associated socio-demographic and clinical factors using logistic regression (LR), random forest (RF), and XGBoost algorithms. …”

Data Sheet 5_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…Missing data were handled using random forest algorithm, feature selection was performed using Boruta algorithm, and SMOTE technique addressed class imbalance. …”

Data Sheet 7_Multidimensional dietary assessment and interpretable machine learning models predict the risk of prediabetes/diabetes and osteoporosis comorbidity in older adults.pdf by Yuwen ShangGuan (22633190)

“…Missing data were handled using random forest algorithm, feature selection was performed using Boruta algorithm, and SMOTE technique addressed class imbalance. …”