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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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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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

Subjects: “…anchor bolt (cable) stress prediction…”
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Deep learning algorithms enable MRI-based scapular morphology analysis with values comparable to CT-based assessments by Hanspeter Hess, Alexandra Oswald, J. Tomás Rojas, Alexandre Lädermann, Matthias A. Zumstein, Kate Gerber

“…A deep learning-based segmentation network was trained with paired CT derived scapula segmentations. An algorithm to fuse multi-plane segmentations was developed to generated high-resolution 3D models of the scapula on which morphological landmark- and axes were predicted using a second deep learning network for morphological analysis. …”
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Reference frame list optimization algorithm in video coding by quality enhancement of the nearest picture by Junyan HUO, Ruipeng QIU, Yanzhuo MA, Fuzheng YANG

“…Interframe prediction is a key module in video coding, which uses the samples in the reference frames to predict those in the current picture, thus helps to represent the complex video by transmitting a small amount of the prediction residual.In lossy video coding, the qualities of reference frames are affected by the quantization distortion, which lead to poor prediction accuracy and performance degradation.Targeted at the low latency video services, a reference frame list optimization algorithm was proposed, which enhanced the quality of the nearest reference frame by a deep learning-based convolutional neural network, and integrated the enhanced reference frame into the reference frame list to improve the accuracy of interframe prediction.Compared with H.265/HEVC reference software HM16.22, the proposed algorithm provides BD-rate savings of 9.06%, 14.92% and 13.19% for Y, Cb and Cr components, respectively.…”
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Research on Predicting Joint Rotation Angles Through Mechanomyography Signals and the Broad Learning System by Yu Bai, Xiaorong Guan, Huibin Li, Shi Cheng, Rui Zhang, Long He

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Development and validation of a nomogram for predicting lung cancer based on acoustic–clinical features by Zhou Lu, Zhou Lu, Jiaojiao Sha, Xunxia Zhu, Xiaoyong Shen, Xiaoyu Chen, Xin Tan, Rouyan Pan, Shuyi Zhang, Shi Liu, Tao Jiang, Jiatuo Xu

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A deep learning based prediction model for effective elastic properties of porous materials by Chang Liu, Ran Guo, Yangming Su

“…Furthermore, a neural network-based machine learning algorithm is established to predict the mechanical properties of porous materials. …”
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Predicting over-the-counter antibiotic use in rural Pune, India, using machine learning methods by Pravin Arun Sawant, Sakshi Shantanu Hiralkar, Yogita Purushottam Hulsurkar, Mugdha Sharad Phutane, Uma Satish Mahajan, Abhay Machindra Kudale

“…METHODS The features of OTC antibiotic use were selected using stepwise logistic, lasso, random forest, XGBoost, and Boruta algorithms. Regression and tree-based models with all confirmed and tentatively important features were built to predict the use of OTC antibiotics. …”
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An interpretable predictive model for bank customers’ income using the eXtreme Gradient Boosting algorithm and the SHAP method: a case study of an Anonymous Chilean Bank by Patricio Salas, Patricio Sáez, Vicente Marchant

“…Feature reduction is accomplished through the implementation of Boruta and BorutaSHAP, ensuring that no predictive power is lost throughout the process. …”
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Construction of a risk prediction model for postoperative deep vein thrombosis in colorectal cancer patients based on machine learning algorithms by Xin Liu, Xingming Shu, Yejiang Zhou, Yifan Jiang

“…Moreover, the SHAP method identified age and preoperative prealbumin as the primary determinants influencing ML model predictions. Finally, the study employed LIME for more precise prediction and interpretation of individual predictions.ConclusionThe machine learning algorithms effectively predicted postoperative lower limb deep vein thrombosis in colorectal cancer patients. …”
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Development and Internal Validation of Machine Learning Algorithms for Predicting Subsequent Contralateral Slipped Capital Femoral Epiphysis in Patients With Unilateral Slips by David P. VanEenenaam, Jr., BS, Carter Hall, BS, Daniel A. Maranho, MD, PhD, Christopher J. DeFrancesco, MD, Eduardo N. Novais, MD, Wudbhav N. Sankar, MD

“…Machine learning (ML) algorithms can be leveraged to identify complex, nonlinear patterns in data and allow for more accurate predictions on which patients may need a prophylactic pin. …”
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Energy consumption reduction for an ultra-low-cost artificial pancreas using an event-trigger MPC strategy by Jhon E. Goez-Mora, Pablo S. Rivadeneira

“…This work aims to evaluate the performance of an impulsive Model Predictive Control (MPC) strategy with an event-triggered (ET) approach implemented in an artificial pancreas (AP) system to determine if insulin injection is necessary, avoiding the execution of the control algorithm and the use of hardware associated to that in each sampling period. …”
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EMPLOYING GENETIC ALGORITHM INSPIRED HYPERPARAMETER OPTIMIZATION IN MOBILE NET V2 ARCHITECTURE by Baljinder Kaur, Manik Rakhra, Nonita Sharma, Monika Mangla

Subjects: “…predictive modeling…”
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Integrative machine learning approach for forecasting lung cancer chemosensitivity: From algorithm to cell line validation by Jinghong Chen, Yonglin Yi, Chunqian Yang, Haoxuan Ying, Jian Zhang, Anqi Lin, Ting Wei, Peng Luo

“…Methods: This study developed a model to predict chemotherapy response in lung cancer patients by integrating multi-omics and clinical data from the Genomics of Drug Sensitivity in Cancer database, employing 45 machine learning algorithms. …”
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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

Subjects: “…water quality prediction|ceemdan decomposition|fuzzy dispersion entropy|mantis search algorithm|hybrid model…”
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A Feature Engineering Framework for Smart Meter Group Failure Rate Prediction by Yihong Li, Xia Xiao, Zhengbo Zhang, Wenao Liu

“…This paper proposes feature engineering including feature construction and feature selection for smart meter group failure rate prediction. First, the basic structure and common fault types of smart meters are introduced. …”
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Research on Offshore Vessel Trajectory Prediction Based on PSO-CNN-RGRU-Attention by Wei Liu, Yu Cao

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Prediction of China’s Silicon Wafer Price: A GA-PSO-BP Model by Jining Wang, Hui Chen, Lei Wang

Subjects: “…China’s silicon wafer price prediction…”
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Heuristic based federated learning with adaptive hyperparameter tuning for households energy prediction by Liana Toderean, Mihai Daian, Tudor Cioara, Ionut Anghel, Vasilis Michalakopoulos, Efstathios Sarantinopoulos, Elissaios Sarmas

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