Hybrid feature selection framework for enhanced credit card fraud detection using machine learning models. by Al Mahmud Siam, Pankaj Bhowmik, Md Palash Uddin

“…To address this, we propose a novel hybrid feature selection framework designed to enhance the performance of machine learning models in credit card fraud detection. …”
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Construction of a machine learning-based interpretable prediction model for acute kidney injury in hospitalized patients by Xiang Yu, WanLing Wang, RiLiGe Wu, XinYan Gong, YuWei Ji, Zhe Feng

“…All the models showed significant net returns according to decision analysis curves, and the XGBoost model achieved the optimal results. …”
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Multivariate Machine Learning Model Based on YOLOv8 for Traffic Flow Prediction in Intelligent Transportation Systems by Fukui Wu, Hanzhong Tan, Linfeng Zhang, Shuangbing Wen, Tao Hu

“…Traffic flow prediction plays a crucial role in Intelligent Transportation Systems (ITS), as it substantially enhances traffic management efficiency, alleviates congestion, and improves road safety. Traditional models often face challenges in addressing the dynamic complexity of modern highway traffic, whereas multivariate machine learning models demonstrate superior predictive accuracy by leveraging diverse data sources. …”
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The role of mitochondria-related genes in hepatocellular carcinoma prognosis: construction of prognostic models based on machine learning by Fei Gao, Fei Teng, Yuxiang Wan, Qiaoli Zhang, Jinchang Huang

“…Results Stepwise Logistic Regression with Gradient Boosting Machine was chosen as the optimal model (area under the curve [AUC] = 0.977). …”
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Machine learning model for prediction of palliative care phases in patients with advanced cancer: a retrospective study by Junchen Guo, Yunyun Dai, Sishan Jiang, Junqingzhao Liu, Xianghua Xu, Yongyi Chen

“…Conclusions The prediction model developed in this study based on the machine learning algorithm showed good performance, offering significant potential for facilitating timely interventions, enhancing symptom management, and optimizing palliative care resource allocation in advanced cancer patients in mainland China.…”
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An Automated Framework for Lane Closure Detection on Highway Using Connected Vehicle Data and Machine Learning Models by Ashutosh Dumka, Raghupathi Kandiboina, Aparna Joshi, Skylar Knickerbocker, Neal Hawkins, Anuj Sharma

“…We employ two machine learning models—support vector machines (SVMs) and k-nearest neighbors (K-NN)—trained on features extracted from these metrics to detect lane closures and provide insights into location and time of start and end. …”
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Development and evaluation of machine learning models for individualized prediction of myopia control efficacy treated with overnight orthokeratology by Lan Zhang, Mingjun Gao, Yiru Wang, Siqi Zhang, Huailin Zhu, Qi Zhao

“…The final features are input into the machine learning model for prediction model construction to predict 1-year axial length elongation. …”
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Spatiotemporal variation and influencing factors of phosphorus in Asia’s longest river based on receptor model and machine learning by Gege Cai, Jiamei Zhang, Wanlu Li, Jiejun Zhang, Yun Liu, Shanshan Xi, Guolian Li, Haibin Li, Xing Chen, Fanhao Song, Fazhi Xie

“…The contribution rate in wet season was ranked as point source pollution (40.13 %) > agricultural pollution (32.74 %) > organic pollutants (3.78 %), while the contribution rate in dry season was ranked as point source pollution (44.88 %) > organic pollutants (13.13 %) > seasonal factor (7.60 %). Machine learning models (e.g., RidgeCV, Random Forest, XGBoost) were used to establish a connection between total phosphorus concentrations and explanatory variables defining influencing factors, aiming to predict total phosphorus concentrations in the Yangtze River. …”
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MRI machine learning model predicts nerve root sedimentation in lumbar stenosis: a prospective study by Qing Wang, Xianping Luo, Deng Li, Yi Zhai, Caiyun Ying

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Hybrid Tree-Based Machine Learning Models for State-of-Charge and Core Temperature Estimation in EV Batteries by Aya Haraz, Khalid Abualsaud, Ahmed M. Massoud

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A robust pressure drop prediction model in vertical multiphase flow: a machine learning approach by Fahd Saeed Alakbari, Mohammed Abdalla Ayoub, M. A. Awad, Tarek Ganat, Mysara Eissa Mohyaldinn, Syed Mohammad Mahmood

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Utilizing machine learning models for predicting outcomes in acute pancreatitis: development and validation in three retrospective cohorts by Kaier Gu, Yang Liu

“…Furthermore, existing in-hospital prediction models exhibit notable limitations. This study leverages machine learning (ML) technology to develop prognosis prediction models for AP patients, encompassing in-hospital mortality, readmission rates, and post-discharge mortality. …”
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Machine learning model for diagnosing salivary gland adenoid cystic carcinoma based on clinical and ultrasound features by Huan-Zhong Su, Zhi-Yong Li, Long-Cheng Hong, Yu-Hui Wu, Feng Zhang, Zuo-Bing Zhang, Xiao-Dong Zhang

“…Abstract Objective To develop and validate machine learning (ML) models for diagnosing salivary gland adenoid cystic carcinoma (ACC) in the salivary glands based on clinical and ultrasound features. …”
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Predicting Oncological and Functional Outcomes by Nephrectomy Type for T1 Renal Tumors Using Machine Learning Models by Dongrul Shin, Maisy Song, Jungyo Suh, Cheryn Song

“…Using machine learning algorithms, we aimed to develop a model to predict both outcomes simultaneously, according to each radical (RN) and partial nephrectomy (PN). …”
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Predicting Quality of Life in People Living with HIV: A Machine Learning Model Integrating Multidimensional Determinants by Meilian Xie, Zhiyun Zhang, Yanping Yu, Li Zhang, Jieli Zhang, Dongxia Wu

“…We therefore aimed to develop and validate machine learning models that predict QoL trend in PLWH, identifying key determinants to inform personalized interventions and optimize long-term well-being. …”
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Enhanced intrusion detection model based on principal component analysis and variable ensemble machine learning algorithm by Ayuba John, Ismail Fauzi Bin Isnin, Syed Hamid Hussain Madni, Farkhana Binti Muchtar

“…This paper proposes a variable ensemble machine learning method to solve the problem and achieve a low variance model with high accuracy and low false alarm. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

“…Various feature selection algorithms were applied to identify the most relevant features, which were then used to train and evaluate machine learning classification models. Model performance was evaluated using a range of classification metrics, including measures of predictive accuracy and diagnostic reliability, with 95% confidence intervals provided to enhance reliability. …”
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Incorporation of visible/near-infrared spectroscopy and machine learning models for indirect assessment of grape ripening indicators by Osama Elsherbiny, Salah El-Hendawy, Salah Elsayed, Abdallah Elshawadfy Elwakeel, Abdullah Alebidi, Xianlu Yue, Wael Mohamed Elmessery, Hoda Galal

“…Abstract The assessment of grape ripeness is pivotal for optimizing harvest timing and ensuring high-quality fruit production. …”
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Development and validation of an interpretable machine learning model for predicting hyperuricemia risk: Based on environmental chemical exposure by Xiaochuan Lu, Huawei Kou, Cong Li, Runqing Zhan, Rongrong Guo, Shengnan Liu, Peixuan Shen, Meiyue Shen, Tingwei Du, Jiaqi Lu, Xiaoli Shen

“…This study is the first to predict the risk of hyperuricemia based on multiple environmental chemical exposures using a machine learning model.…”
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A predictive machine-learning model for clinical decision-making in washed microbiota transplantation on ulcerative colitis by Sheng Zhang, Gaochen Lu, Weihong Wang, Qianqian Li, Rui Wang, Zulun Zhang, Xia Wu, Chenchen Liang, Yujie Liu, Pan Li, Quan Wen, Bota Cui, Faming Zhang

“…This study aimed to build a machine learning model on washed microbiota transplantation (WMT) for ulcerative colitis (UC), providing patients and clinicians with a new evaluation system to optimize clinical decision-making.MethodsPatients with UC who underwent WMT via mid-gut or colonic delivery route at an affiliated hospital of Nanjing Medical University from April 2013 to June 2022 were recruited. …”
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