Prediction of risk for acute kidney injury and its progression to mortality in obese patients admitted to ICU postoperatively by LI Qiang, LI Qiang, MU Guo, MU Guo, WANG Wenzhang

“…After data cleaning and preprocessing, Boruta feature selection was applied, followed by the construction of prediction models using 7 machine learning algorithms, that is, Gradient Boosting Machine (GBM), Generalized Linear Model (GLM), k-Nearest Neighbors (KNN), Naïve Bayes (NB), Neural Network (NNET), Support Vector Machine (SVM), and XGBoost. …”
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Deep Temporal Clustering of Pathological Gait Patterns in Post-Stroke Patients Using Joint Angle Trajectories: A Cross-Sectional Study by Gyeongmin Kim, Hyungtai Kim, Yun-Hee Kim, Seung-Jong Kim, Mun-Taek Choi

“…Through this method, six optimal clusters were selected with a silhouette score of 0.2831, which is a relatively higher value compared to other clustering algorithms. To clarify the characteristics of the selected groups, in-depth statistics of spatiotemporal, kinematic, and clinical features are presented in the results. …”
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Enhancing Yield Estimation and Field Zoning Accuracy in Precision Agriculture Using Solar-Powered Drone-Based Remote Sensing by Abbas Haider Mohammed, Obaid Mohammed Kadhim, Vittalaiah A.

“…The system processes this data using advanced machine learning algorithms to forecast crop yields and generate detailed field zoning maps, enabling optimized resource allocation and improved farm management. …”
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Optimisation of the adaptive neuro-fuzzy inference system for adjusting low-cost sensors PM concentrations by Martina Casari, Piotr A. Kowalski, Laura Po

“…The paper also explores various ANFIS configurations, including two distinct optimization algorithms, and investigates the impact of the number and type of membership functions on the fuzzy system's performance. …”
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Coordinating environmental genomics and geochemistry reveals metabolic transitions in a hot spring ecosystem. by Wesley D Swingley, D'Arcy R Meyer-Dombard, Everett L Shock, Eric B Alsop, Heinz D Falenski, Jeff R Havig, Jason Raymond

“…We have also assigned environmental genome sequences to individual microbial community members by complementing traditional homology-based assignment with nucleotide word-usage algorithms, allowing more than 70% of all reads to be assigned to source organisms. …”
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Directed carbapenemase testing is no longer just for Enterobacterales: cost, labor, and workflow assessment of expanding carbapenemase testing to carbapenem-resistant P. aeruginosa by Christian M. Gill, Poonam Rajkotia, Amity L. Roberts, Fred C. Tenover, David P. Nicolau

“…Supplemental phenotypic algorithms can be implemented to curb the cost of P. aeruginosa carbapenemases testing by identifying isolates most likely to harbour carbapenemases.…”
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Development and validation of a machine learning-based prediction model for hepatorenal syndrome in liver cirrhosis patients using MIMIC-IV and eICU databases by Fengwei Yao, Ji Luo, Qian Zhou, Luhua Wang, Zhijun He

“…By integrating the MIMIC-IV database and machine learning algorithms, we developed an effective predictive model for HRS in liver cirrhosis patients, providing a robust tool for early clinical intervention.…”
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A graphical modelling approach to the dissection of highly correlated transcription factor binding site profiles. by Robert Stojnic, Audrey Qiuyan Fu, Boris Adryan

“…Here, we develop a novel computational method, the Neighbourhood Consistent PC (NCPC) algorithms, which deal with these scenarios much more effectively than existing methods do. …”
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Palmitoylation-related gene ZDHHC22 as a potential diagnostic and immunomodulatory target in Alzheimer’s disease: insights from machine learning analyses and WGCNA by Sanying Mao, Xiyao Zhao, Lei Wang, Yilong Man, Kaiyuan Li

“…This study applied WGCNA along with three machine learning algorithms—random forest, LASSO regression, and SVM–RFE—to further select key PRGs (KPRGs). …”
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Adaptación de un Recomendador de Filtro Colaborativo Basado en el Usuario para la Creación de un Recomendador de Materias de Pregrado Basado en el Historial Académico de los Estudi... by J. Del Pino, G. Salazar, V. Cedeño

“…A set of tests will be conducted to measure its effectiveness, using two different similarity algorithms to recommend courses to a student for the sixth semester of the Electronics and Telecommunications career offered by FIEC - ESPOL. …”
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Integrating SEResNet101 and SE-VGG19 for advanced cervical lesion detection: a step forward in precision oncology by Yan Ye, Yuanyuan Chen, Jiajia Pan, Peipei Li, Feifei Ni, Haizhen He

“…Conclusion Our results indicate that SEResNet101 offers a promising enhancement over existing screening methods, integrating advanced deep learning algorithms to significantly improve the precision of cervical lesion classification. …”
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Constructing multilayer PPI networks based on homologous proteins and integrating multiple PageRank to identify essential proteins by He Zhao, Huan Xu, Tao Wang, Guixia Liu

“…Results To address these issues, we propose a novel model, MLPR, which constructs a multilayer PPI network based on homologous proteins and integrates multiple PageRank algorithms to identify essential proteins. This study combines homologous protein data from three species to construct interlayer transition matrices and assigns weights to interlayer edges by integrating the biological attributes of homologous proteins and cross-species GO annotations. …”
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Multi-Trait Phenotypic Analysis and Biomass Estimation of Lettuce Cultivars Based on SFM-MVS by Tiezhu Li, Yixue Zhang, Lian Hu, Yiqiu Zhao, Zongyao Cai, Tingting Yu, Xiaodong Zhang

“…Based on the Structure-from-Motion Multi-View Stereo (SFM-MVS) algorithms, a high-precision three-dimensional point cloud model was reconstructed from multi-view RGB image sequences, and 12 phenotypic parameters, such as plant height, crown width, were accurately extracted. …”
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Enhancing Privacy in IoT-Enabled Digital Infrastructure: Evaluating Federated Learning for Intrusion and Fraud Detection by Amogh Deshmukh, Peplluis Esteva de la Rosa, Raul Villamarin Rodriguez, Sandeep Dasari

“…In this analysis, the UNSW-NB15 and credit datasets were employed, utilizing precision, recall, accuracy, F1-score, ROC, and AUC as performance indicators to demonstrate the effectiveness of the proposed strategy using FedAvg, FedProx, and FedOpt. The proposed algorithms were subjected to an empirical study, which revealed significant performance benefits when using the flower framework. …”
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Development of a Multi-Source Satellite Fusion Method for XCH₄ Product Generation in Oil and Gas Production Areas by Lu Fan, Yong Wan, Yongshou Dai

“…Finally, the challenges that emerged from the study were discussed and summarized, and it was envisioned that, in the future, with the advancement of satellite technology and algorithms, it would be possible to obtain more accurate and high-resolution datasets of methane concentration and apply such datasets to a wide range of fields, with the expectation that significant contributions could be made to reducing methane emissions and combating climate change.…”
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Acoustic-Emergent Phonology in the Amplitude Envelope of Child-Directed Speech. by Victoria Leong, Usha Goswami

“…Here we present the Spectral Amplitude Modulation Phase Hierarchy (S-AMPH) model, a set of algorithms for deriving the dominant AM patterns in child-directed speech (CDS). …”
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Enhancing Crop Health: Advanced Machine Learning Techniques for Prediction Disease in Palm Oil Tree by Nandy Manish, Kumar Yalakala Dinesh

“…This study builds predictive models by using a palmd database comprised of the large datasets of palm oil tree health indicators, environmental factors and historical disease outbreaks to identify early signs of disease with high accuracy.To analyze both structured as well as unstructured data multiple machine learning algorithms were used such as Random Forest, Support Vector Machines, Convolution Neural Networks. …”
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A conceptual digital twin framework for supply chain recovery and resilience by Oluwagbenga Victor Ogunsoto, Jessica Olivares-Aguila, Waguih ElMaraghy

“…In the first phase, machine learning algorithms, including logistic regression and Long Short-Term Memory (LSTM), were trained on Kerala India's precipitation data to predict floods. …”
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Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection by Jie Zhuang, Quan Wang

“…Among the feature selection algorithms, the least absolute shrinkage and selection operator (LASSO) and stepwise regression (Stepwise) methods outperformed others. …”
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Combining Process Mining and Process Simulation in Healthcare: A Literature Review by Evelyn Salas, Michael Arias, Santiago Aguirre, Eric Rojas

“…By reviewing distinct scholarly databases, 31 research studies were selected for analysis, from which it was possible to characterize case studies, techniques, tools, perspectives and algorithms, as well as to identify key limitations. …”
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