Machine learning insights into early mortality risks for small cell lung cancer patients post-chemotherapy by Min Liang, Min Liang, Fuyuan Luo

“…Predictive modeling was performed using advanced machine learning algorithms, including XGBoost, Multilayer Perceptron, K-Nearest Neighbor, and Random Forest. …”
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On the principles of building a model of a specialist – a graduate of a pedagogical university by K. S. Kаtаеv, S. G. Kаtаеv, I. V. Kаmenskaya

“…The reasonableness of the obtained results of the study, the availability of a variety of algorithms for data interpretation indicate the real possibility of using in practice the proposed structure of the model, including the way of organising data as a monitoring system.…”
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Multi-Cell Displacement Measurement During the Assembly of Automotive Power Batteries Based on Machine Vision by Yueda Xu, Yanfeng Xing, Hongbo Zhao, Yufang Lin, Lijia Ren, Zhihan Zhou

“…Compared to other feature matching algorithms, this method can more consistently and accurately detect feature points and calculate displacements, meeting the positioning accuracy requirements for the stack pole ear in the actual assembly process. …”
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Dynamic Reliability Management for FPGA-Based Systems by Jahanzeb Anwer, Sebastian Meisner, Marco Platzner

“…Moreover, the redundant circuit implementations vary in structure and resource usage with the redundancy insertion algorithms as well as number of used redundant stages. …”
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Integrated Approach for Biomarker Discovery and Mechanistic Insights into the Co-Pathogenesis of Type 2 Diabetes Mellitus and Non-Hodgkin Lymphoma by Zhu Y, Liu J, Wang B

“…Topological analysis and machine learning algorithms were applied to refine hub gene selection. …”
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New Predictive Models for the Computation of Reinforced Concrete Columns Shear Strength by Anthos I. Ioannou, David Galbraith, Nikolaos Bakas, George Markou, John Bellos

“…Significantly improved predictive models are proposed herein through the implementation of machine learning (ML) algorithms on refined datasets. Three ML models, LREGR, POLYREG-HYT, and XGBoost-HYT-CV, were used to develop different predictive models that were able to compute the shear strength of RC columns. …”
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A Novel Immune-Related Three-Gene Signature and Immune Infiltration Insights in Psoriasis and Chronic Kidney Disease by Yin T, Zhang T, Ma L

“…Subsequently, six hub genes were determined using five topological algorithms. The responses of these two diseases exhibited similar changes in immune reactions. …”
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The Application of CA and PCA to the Evaluation of Lipophilicity and Physicochemical Properties of Tetracyclic Diazaphenothiazine Derivatives by Anna Nycz–Empel, Katarzyna Bober, Mirosław Wyszomirski, Ewa Kisiel, Andrzej Zięba

“…Using computer programs, based on different computational algorithms, theoretical values of lipophilicity (AClogP, ALOGP, ALOGPs, miLogP, MLOGP, XLOGP2, and XLOGP3) as well as molecular descriptors (molecular weight, volume of a molecule, dipole moment, polar surface, and energy of HOMO orbitals and LUMO orbitals) and parameters of biological activity: human intestinal absorption (HIA), plasma protein binding (PPB), and blood-brain barrier (BBB), were determined. …”
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Facilitating automated fact-checking: a machine learning based weighted ensemble technique for claim detection by Md. Rashadur Rahman, Rezaul Karim, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Gahangir Hossain, Tetsuya Shimamura

“…To determine the optimal model and feature representation for claim detection, various machine learning algorithms were evaluated using BoW, TF-IDF, Word2Vec, and FastText features. …”
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A novel machine learning-based immune prognostic signature for improving clinical outcomes and guiding therapy in colorectal cancer: an integrated bioinformatics and experimental s... by Yuanchun Zhao, Dexu Xun, Jiajia Chen, Xin Qi

“…Considering the high incidence and mortality of colorectal cancer (CRC), in this study, an integrated machine learning survival framework incorporating 93 different algorithmic combinations was utilized to determine the optimal strategy for developing an immune-related prognostic signature (IRPS) based on the average C-index across the four CRC cohorts. …”
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Cerebral 18F-FDG PET in macrophagic myofasciitis: An individual SVM-based approach. by Paul Blanc-Durand, Axel Van Der Gucht, Eric Guedj, Mukedaisi Abulizi, Mehdi Aoun-Sebaiti, Lionel Lerman, Antoine Verger, François-Jérôme Authier, Emmanuel Itti

“…<h4>Conclusion</h4>We developed an original and individual approach including a SVM to classify patients between healthy or MMF metabolic brain profiles using 18F-FDG-PET. Machine learning algorithms are promising for computer-aided diagnosis but will need further validation in prospective cohorts.…”
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Energy consumption prediction using modified deep CNN-Bi LSTM with attention mechanism by Adel Binbusayyis, Mohemmed Sha

“…To enhance prediction accuracy, a proposed smart city system utilizes the Household Energy Consumption dataset, employing deep learning algorithms. In the beginning, data pre-processing addresses missing values and performs feature scaling for normalizing independent variables. …”
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Development and external validation of machine learning-based models to predict patients with cellulitis developing sepsis during hospitalisation by Li Hu, Xilingyuan Chen, Rentao Yu

“…This study was designed to develop and compare different models for predicting patients with cellulitis developing sepsis during hospitalisation.Design This is a retrospective cohort study.Setting This study included both the development and the external-validation phases from two independent large cohorts internationally.Participants and methods A total of 6695 patients with cellulitis in the Medical Information Mart for Intensive care (MIMIC)-IV database were used to develop models with different machine-learning algorithms. The best models were selected and then externally validated in 2506 patients with cellulitis from the YiduCloud database of our university. …”
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A Hybrid Model for Psoriasis Subtype Classification: Integrating Multi Transfer Learning and Hard Voting Ensemble Models by İsmail Anıl Avcı, Merve Zirekgür, Barış Karakaya, Betül Demir

“…The feature set was divided into 80% training and 20% testing subsets and evaluated using a hard voting classifier consisting of logistic regression, random forest, support vector classifier, k-nearest neighbors, and gradient boosting algorithms. <b>Results:</b> The proposed hybrid approach achieved 93.14% accuracy, 96.75% precision, and an F1 score of 91.44%, demonstrating superior performance compared to individual transfer learning models. …”
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Identification of an Inflammatory Response-Related Gene Signature to Predict Survival and Immune Status in Glioma Patients by Zhaoyue Yan, Yushuai Gao, Jinliang Yu, Zhiyuan Shen, Xingyao Bu

“…The differences in clinical correlations, immune infiltrate types, immunotherapeutic response predictions, and pathway enrichment among subgroups were investigated via bioinformatic algorithms. Results. In total, 37 DE-IRRGs were determined, of which 31 were found to be associated with survival. …”
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Machine Learning Models for Spring Discharge Forecasting by Francesco Granata, Michele Saroli, Giovanni de Marinis, Rudy Gargano

“…Three different machine learning algorithms were used for spring discharge forecasting in this comparative study: M5P regression tree, random forest, and support vector regression. …”
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Free-space optical spiking neural network. by Reyhane Ahmadi, Amirreza Ahmadnejad, Somayyeh Koohi

“…To enhance signal integrity, we employ high-quality optical components, error correction algorithms, adaptive optics, and noise-resistant coding schemes. …”
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Surprise Bug Report Prediction Utilizing Optimized Integration with Imbalanced Learning Strategy by Hui Li, Yang Qu, Shikai Guo, Guofeng Gao, Rong Chen, Guo Chen

“…Then these datasets after balancing are used to train three selected classifiers which are built by three different classification algorithms and predict the datasets with unknown type. …”
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Relationship Between Weight Status and Health-Related Quality of Life in School-age Children in China by Mandana Zanganeh, Peymané Adab, Bai Li, Miranda Pallan, Wei J. Liu, Lin Rong, Wei Liu, James Martin, Kar K. Cheng, Emma Frew

“…CHU-9D-CHN utility scores were generated using 2 scoring algorithms (UK and Chinese tariffs). Height and weight measures were taken at school by trained researchers using standardized methods, and BMI _z_ scores were calculated using the World Health Organization 2007 growth charts. …”
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Measuring Passenger Car Equivalents (PCE) for Heavy Vehicle on Two Lane Highway Segments Operating Under Various Traffic Conditions by Pan Lu, Zijian Zheng, Denver Tolliver, Danguang Pan

“…This study introduces an analytical model, combining a headway-based and a delay-based algorithms, for estimating PCEs of HV on a TLTW highway. …”
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