Predicting COVID-19 severity in pediatric patients using machine learning: a comparative analysis of algorithms and ensemble methods by Babak Pourakbari, Setareh Mamishi, Sepideh Keshavarz Valian, Shima Mahmoudi, Reihaneh Hosseinpour Sadeghi, Mohammad Reza Abdolsalehi, Mahmoud Khodabandeh, Mohammad Farahmand

“…This study evaluates the performance of machine learning algorithms in predicting disease severity among pediatrics. …”
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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Moreover, among all the hyperparameter-optimized algorithms, adaboost algorithm outperformed all the other hyperparameter-optimized algorithms. …”
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Efficient Recovery of Linear Predicted Coefficients Based on Adaptive Steepest Descent Algorithm in Signal Compression for End-to-End Communications by Abel Kamagara, Abbas Kagudde, Baris Atakan

“…Herein, the steepest descent algorithm is applied at the receiver to decode the affected linear predicted coefficients. …”
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Prediction of the Punching Load Strength of SCS Slabs with Stud-Bolt Shear Connectors Using Numerical Modeling and GEP Algorithm by Mehdi Yousefi, Mohammad Golmohammadi, Seyed Hashem Khatibi, Majid Yaghoobi

“…Finally, using the experimental setup and gene expression programming (GEP) algorithm, several numerical models were planned to predict the maximum strength of the slabs and a simple relation was proposed. …”
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An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm by Yuan Jin, Yunliang Lai, Azadeh Noori Hoshyar, Nisreen Innab, Meshal Shutaywi, Wejdan Deebani, A. Swathi

“…Although recent studies propose comprehensive automated diagnostic systems, these systems tend to focus on one aspect, such as feature selection, prioritization, or predictive accuracy. A more complete approach that considers all of these factors can improve the efficiency of a cardiac prediction system. …”
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Conversion Prediction in Google Search Ads Keyword Selection Using the K-Nearest Neighbor and C4.5 Algorithms by Muhammad Sya'ban Harahap, Alva Hendi Muhammad

“…This study was conducted to analyze and compare the effectiveness of two algorithms—K-Nearest Neighbor (K-NN) and C4.5—in predicting keyword conversion on the Google Ads platform. …”
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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…This study evaluates the performance of two machine learning algorithms, namely Support Vector Machine (SVM) and Decision Tree (DT), in predicting heart disease risk by applying undersampling techniques to handle data imbalance. …”
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Predicting indoor temperature of solar green house by machine learning algorithms: A comparative analysis and a practical approach by Wenhe Liu, Tao Han, Cong Wang, Feng Zhang, Zhanyang Xu

“…This study focuses on a solar greenhouse located at the experimental base of Shenyang Agricultural University in Shenyang, Liaoning Province, to develop multi-step temperature prediction models based on machine learning algorithms. …”
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A Prediction of the Shooting Trajectory for a Tuna Purse Seine Using the Double Deep Q-Network (DDQN) Algorithm by Daeyeon Cho, Jihoon Lee

“…This study proposes a method for predicting shooting trajectories using the Double Deep Q-Network (DDQN) algorithm. …”
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An Effective Approach to Promote Air Traveler Repurchasing Using the Random Forest Algorithm: Predictive Model Design and Utility Evaluation by Zhenyuan Zhang, Yanhong Chen, Luning Liu

“…The results show that the proposed model framework is better than the prediction results of the other algorithms. In addition, the proposed model framework was verified through a real case of an airline in China. …”
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Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus by Lu-Xi Zou, Xue Wang, Zhi-Li Hou, Ling Sun, Jiang-Tao Lu

“…More sensitive methods for early DKD prediction are urgently needed. This study aimed to set up DKD risk prediction models based on machine learning algorithms (MLAs) in patients with type 2 DM (T2DM).Methods The electronic health records of 12,190 T2DM patients with 3-year follow-ups were extracted, and the dataset was divided into a training and testing dataset in a 4:1 ratio. …”
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TCN-LSTM-MHSA model optimized by improved slime mould algorithm for stress prediction of roadway anchor bolts (cables) by QI Junyan, CHE Yuhao, WANG Lei, YUAN Ruifu

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Chemometric and meta-heuristic algorithms to find optimal wavelengths and predict ‘Red Delicious’ apples traits using Vis-NIR by Mahsa S. Razavi, Vali Rasouli Sharabiani, Mohammad Tahmasebi, Silvia Grassi, Mariusz Szymanek

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Unleashing quantum algorithms with Qinterpreter: bridging the gap between theory and practice across leading quantum computing platforms by Wilmer Contreras-Sepúlveda, Braulio Misael Villegas-Martínez, Sandra Gesing, José Javier Sánchez-Mondragón, Juan Carlos Sánchez-Pérez, Claudia Andrea Vidales-Basurto, J. Jesús Escobedo-Alatorre, Angel David Torres-Palencia, Omar Palillero-Sandoval, Jacob Licea-Rodriguez, Néstor Lozano-Crisóstomo, Julio César García-Melgarejo, Eddie Nelson Palacios-Perez

“…Due to the inherent complexity and divergence from classical computing, several major quantum computing libraries have been developed to implement quantum algorithms, namely IBM Qiskit, Amazon Braket, Cirq, PyQuil, and PennyLane. …”
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Prediction of Liquefaction-Induced Lateral Displacements Using Hybrid GBRT and EOA by Arash Ziaie, Bahareh Mehdizadeh, Farzad Safi Jahanshahi, Nazanin Ahmadi, Ali Reza Ghanizadeh

“…This research employs the Gradient Boosting Regression Tree (GBRT) approach, tuned through the Equilibrium Optimization Algorithm (EOA), to estimate LILD. A dataset containing 247 data points was used to build the predictive model. …”
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Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

“…Considering these multiple influencing factors, herein, a method is proposed to predict the milling stability and determine optimal machining parameters based on a bootstrap aggregating (bagging) procedure and the non-dominated sorting genetic algorithm–Ⅱ (NSGA–Ⅱ). …”
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Alzheimer’s Disease Prediction Using Fisher Mantis Optimization and Hybrid Deep Learning Models by Sameer Abbas, Mustafa Yeniad, Javad Rahebi

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Research on short-term precipitation forecasting method based on CEEMDAN-GRU algorithm by Hua Xu, Zongkai Guo, Yu Cao, Xu Cheng, Qiong Zhang, Dan Chen

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Development of a MVI associated HCC prognostic model through single cell transcriptomic analysis and 101 machine learning algorithms by Jiayi Zhang, Zheng Zhang, Chenqing Yang, Qingguang Liu, Tao Song

“…Additionally, we affirmed the predictive precision and superiority of our model through a meta-analysis against existing HCC models. …”
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Medium- and Long-term Runoff Prediction Based on SMA-LSSVM by TIAN Jinghuan, LI Congxin, LI Ang

Subjects: “…slime mold algorithm (SMA)…”
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