Applying machine learning algorithms to explore the impact of combined noise and dust on hearing loss in occupationally exposed populations by Yong Li, Xin Sun, Yongtao Qu, Shuling Yang, Yueyi Zhai, Yan Qu

“…Chi-square and Mann-Whitney U tests examined variables, and multivariate logistic regression determined ONIHL risk factors. Machine learning algorithms like Logistic Regression and Random Forest were developed, optimized, and evaluated. …”
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Investigation & analysis of Electrical Discharge Machining on Titanium Diboride Ceramic material with various Electrode materials and dielectric fluids by Karthik S, Sivakumar Annamalai

“…Its strength poses a problem to traditional machining methods. This work aims to compare two different dielectric fluids and four different electrode materials to improve EDM process parameters in TiB _2 material. …”
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Identification of novel potential hypoxia-inducible factor-1α inhibitors through machine learning and computational simulations by Yuxiang He, Shuning Diao, Shengzhen Hou, Taiying Li, Wenhui Meng, Jinping Zhang

“…The virtual screening was conducted in three sequential stages, applying the following selection criteria sequentially: an activity prediction score greater than or equal to 0.8, a stronger binding affinity, and an MM-PBSA binding free energy lower than the reference compound.Results and DiscussionWe retrieved 361 compounds with HIF-1α inhibitory activity data from the ChEMBL database for the construction and evaluation of machine learning models. Among the six constructed models, the random forest model based on RDKit molecular descriptor with the optimal comprehensive performance was employed for virtual screening. …”
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3D Printing of chewable oral tablets using drug nanosuspension inks: an experimental and machine learning study by Hang Truong, Nikki Rodriguez, Alperen Abaci, Gulenay Guner, Joshua Young, Ecevit A. Bilgili, Murat Guvendiren

“…A Gradient Boosting Regressor (GBR) model improved predictions (R² = 0.94, RMSE = 52 µm) and enabled inverse prediction of printing settings for target dimensions. …”
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Explainable machine learning to compare the overall survival status between patients receiving mastectomy and breast conserving surgeries by Betelhem Bizuneh Asfaw, Eyachew Misganew Tegaw

“…To compare the overall survival status of breast cancer patients undergoing Mastectomy versus BCS using ML models and SHAP values, identifying key predictors for survival. …”
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Optimized hybrid deep learning for cross-linguistic sentiment analysis: a novel approach by Vipin Jain, Lokesh Malviya, Anjana .S

“…This paper proposes an optimized hybrid deep learning model for multilingual sentiment analysis, leveraging the Grey Wolf Optimization (GWO) algorithm to enhance the model’s performance. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…A literature review was conducted to obtain 18 PCD-related genes, which were intersected with DEGs to identify DEGs associated with specific types of PCD. Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
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Enhancing phishing detection with dynamic optimization and character-level deep learning in cloud environments by Vishnukumar Ravula, Mangayarkarasi Ramaiah

“…To address these emerging threats, this study introduces a novel Dynamic Arithmetic Optimization Algorithm with Deep Learning-Driven Phishing URL Classification (DAOA-DLPC) model for cloud-enabled IoV infrastructure. …”
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Integrating Genetic Algorithm and Geographically Weighted Approaches into Machine Learning Improves Soil pH Prediction in China by Wantao Zhang, Jingyi Ji, Binbin Li, Xiao Deng, Mingxiang Xu

“…This study integrates Geographic Weighted Regression (GWR) with three ML models (Random Forest, Cubist, and XGBoost) and designs and develops three geographically weighted machine learning models optimized by Genetic Algorithms to improve the prediction of soil pH values. …”
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Enhanced prediction of ventilator-associated pneumonia in patients with traumatic brain injury using advanced machine learning techniques by Negin Ashrafi, Armin Abdollahi, Kamiar Alaei, Maryam Pishgar

“…To address class imbalance, the Synthetic Minority Oversampling Technique (SMOTE) was applied within a five-fold cross-validation framework, ensuring a balanced training set while maintaining an unbiased validation process. Six machine learning models, including Support Vector Machine, Logistic Regression, Random Forest, XGBoost, Artificial Neural Network, and AdaBoost, were trained using extensive hyperparameter tuning. …”
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Incorporating soil moisture data into a machine learning framework improved the predictive accuracy of corn yields in the U.S. by Bishwoyog Bhattarai, Zachary Leasor, André Fróes de Borja Reis

“…We hypothesize that incorporating soil moisture and temperature data from land surface models into a ML framework will enhance accuracy of corn yield predictions. …”
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An enhanced alpha evolution moss growth optimizer for prognostic prediction in spontaneous intracerebral hemorrhage by Lingxian Hou, Yongsheng Wang, Xiuqi Lin, Chengye Li, Huangrong Guo, Congcong Jin, Yi Chen, Huiling Chen, Jing Ji, Wenzong Zhu

“…Current prognostic models, such as clinical scoring systems, often fail to leverage imaging data fully and struggle with non-linear relationships, necessitating advanced machine-learning solutions. …”
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PERFORMANCE COMPARISON OF GRADIENT-BASED CONVOLUTIONAL NEURAL NETWORK OPTIMIZERS FOR FACIAL EXPRESSION RECOGNITION by Sri Nurdiati, Mohamad Khoirun Najib, Fahren Bukhari, Refi Revina, Fitra Nuvus Salsabila

“…A convolutional neural network (CNN) is one of the machine learning models that achieve excellent success in recognizing human facial expressions. …”
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Machine learning-guided integration of fixed and mobile sensors for high resolution urban PM2.5 mapping by Tianshuai Li, Xin Huang, Qingzhu Zhang, Xinfeng Wang, Xianfeng Wang, Anbao Zhu, Zhaolin Wei, Xinyan Wang, Haolin Wang, Jiaqi Chen, Min Li, Qiao Wang, Wenxing Wang

“…The results of multi-model coupling indicated that secondary inorganic aerosols were the primary driving factors for PM2.5 pollution in Jinan. …”
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Thermal performance analysis of a heat exchanger with a novel turbulator insert by using machine learning method by Jiangbo Wang, Chenzhe Li, Liangcai Zeng, Ting Fu, Kai Liu

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Sine Cosine Optimization With Deep Learning–Driven Object Detector for Visually Impaired Persons by Hadeel Alsolai, Fahd N. Al-Wesabi, Abdelwahed Motwakel, Suhanda Drar

“…Both exploit typical machine learning (ML) approaches and utilize deep learning (DL) models to execute object detection methods. …”
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CodonTransformer: a multispecies codon optimizer using context-aware neural networks by Adibvafa Fallahpour, Vincent Gureghian, Guillaume J. Filion, Ariel B. Lindner, Amir Pandi

“…Nevertheless, natural sequences optimized through evolution provide a rich source of data for machine learning algorithms to explore the underlying rules. …”
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A Novel Method for News Recommendation on Websites Using the Clustered-Vectors Optimization Algorithm by Piyanuch Chaipornkaew, Thepparit Banditwattanawong

“…This research introduces a recommendation model for news content utilizing a novel machine learning technique known as the “Clustered-Vectors Optimization (CVO)” algorithm. …”
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Waiting Experience: Optimization of Feedback Mechanism of Voice User Interfaces Based on Time Perception by Junfeng Wang, Yue Li, Shuyu Yang, Shiyu Dong, Jialin Li

“…Based on that, a linear regression model is proposed to define the optimal feedback time of VUI. …”
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Applicability of Machine Learning and Mathematical Equations to the Prediction of Total Organic Carbon in Cambrian Shale, Sichuan Basin, China by Majia Zheng, Meng Zhao, Ya Wu, Kangjun Chen, Jiwei Zheng, Xianglu Tang, Dadong Liu

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