Obesity Related Mortality in the Next Generation: Projections Based on Machine Learning for Young Americans (1999–2035) by Hassam Ali, Waqas Rasheed, Vishali Moond, Dushyant Singh Dahiya, Abdulazeez Swaiti, Manesh Kumar Gangwani, Umar Hayat, Rashmi Advani

“…Future mortality rates were forecasted using an optimal Autoregressive Integrated Moving Average (ARIMA) model. …”
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Fog Service Placement Optimization: A Survey of State-of-the-Art Strategies and Techniques by Hemant Kumar Apat, Veena Goswami, Bibhudatta Sahoo, Rabindra K. Barik, Manob Jyoti Saikia

“…In the present survey, we first describe the fundamental and mathematical aspects of the three-layer IoT–fog–cloud computing model. Then, we classify the IoT application model based on different attributes that help to find the optimal computing node. …”
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Inversion of Crop Water Content Using Multispectral Data and Machine Learning Algorithms in the North China Plain by Zhenghao Zhang, Gensheng Dou, Xin Zhao, Yang Gao, Saisai Liu, Anzhen Qin

“…Among the five machine learning methods, random forest (RF) showed the best performance across the three growth stages, with its coefficient of determination (R²) of 0.80, or an increase by 20.1% than those of other models. …”
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Dominant Tree Species Mapping Using Machine Learning Based on Multi-Temporal and Multi-Source Data by Heyi Guo, Sornkitja Boonprong, Shaohua Wang, Zhidong Zhang, Wei Liang, Min Xu, Xinwei Yang, Kaimin Wang, Jingbo Li, Xiaotong Gao, Yujie Yang, Ruichen Hu, Yu Zhang, Chunxiang Cao

“…Classification employed Random Forest, XGBoost, and deep learning models, with performance evaluated through out-of-bag estimation and cross-validation. …”
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Deep learning-enhanced anti-noise triboelectric acoustic sensor for human-machine collaboration in noisy environments by Chuanjie Yao, Suhang Liu, Zhengjie Liu, Shuang Huang, Tiancheng Sun, Mengyi He, Gemin Xiao, Han Ouyang, Yu Tao, Yancong Qiao, Mingqiang Li, Zhou Li, Peng Shi, Hui-jiuan Chen, Xi Xie

“…However, conventional microphone-based systems remain challenging for complex human-machine collaboration in noisy environments. Herein, an anti-noise triboelectric acoustic sensor (Anti-noise TEAS) based on flexible nanopillar structures is developed and integrated with a convolutional neural network-based deep learning model (Anti-noise TEAS-DLM). …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…The core of our methodology involves a novel algorithm featuring an Efficient-Unet based Deep Learning model for the precise segmentation of NSR areas. …”
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Targeted urinary metabolomics combined with machine learning to identify biomarkers related to central carbon metabolism for IBD by Miao-Lin Lei, Guan-Wei Bi, Xiao-Lin Yin, Xiao-Lin Yin, Yue Wang, Yue Wang, Yue Wang, Zi-Ru Sun, Zi-Ru Sun, Zi-Ru Sun, Xin-rui Guo, Hui-peng Zhang, Xiao-han Zhao, Feng Li, Feng Li, Yan-Bo Yu

“…The optimal diagnostic model achieved a mean AUC of 0.84 for UC and 0.93 for CD. …”
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Multimodal Artificial Intelligence in Medical Diagnostics by Bassem Jandoubi, Moulay A. Akhloufi

“…We then categorize key fusion strategies used to integrate information from multiple modalities and overview representative model architectures, from hybrid designs and transformer-based vision-language models to optimization-driven and EHR-centric frameworks. …”
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Bio inspired feature selection and graph learning for sepsis risk stratification by D. Siri, Raviteja Kocherla, Sudharshan Tumkunta, Pamula Udayaraju, Krishna Chaitanya Gogineni, Gowtham Mamidisetti, Nanditha Boddu

“…Abstract Sepsis remains a leading cause of mortality in critical care settings, necessitating timely and accurate risk stratification. However, existing machine learning models for sepsis prediction often suffer from poor interpretability, limited generalizability across diverse patient populations, and challenges in handling class imbalance and high-dimensional clinical data. …”
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The algorithm of the engineering method of parameter optimization dump working equipment of the motor grader by Ignatov S.D.

“…To address this issue, it is advisable to use mathematical modeling, numerical optimization methods, and load analysis. …”
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PCA-GWO-KELM Optimization Gait Recognition Indoor Fusion Localization Method by Xiaoyu Ji, Xiaoyue Xu, Suqing Yan, Jianming Xiao, Qiang Fu, Kamarul Hawari Bin Ghazali

“…Then, constructing PCA-GWO-KELM optimization gait recognition algorithms to obtain important features, the model parameters of the kernel-limit learning machine are optimized by the gray wolf optimization algorithm. …”
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Performance Analysis and Operation Parameter Optimization of Shaker-Type Harvesting for Camellia Fruits by Qiaoming Gao, Jianfeng Han, Shan Zeng, Yu Wang, Wei Wei, Dongxue Wang, Hang Ye, Jing Lu, Haoxiang Zeng

“…To this end, a dynamic model of the camellia osmantha tree and a self-developed shaker-type harvesting machine were used as research subjects. …”
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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

“…The features are optimized using a Taylor-based African Vulture Optimization Algorithm (AVOA) and classified using a Bilinear Convolutional Attention Network (BCAN). …”
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Automated reinforcement learning for sequential ordering problem using hyperparameter optimization and metalearning by André Luiz Carvalho Ottoni

“…Abstract AutoML systems seek to assist Artificial Intelligence users in finding the best configurations for machine learning models. Following this line, recently the area of Automated Reinforcement Learning (AutoRL) has become increasingly relevant, given the growing increase in applications for reinforcement learning algorithms. …”
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A metaheuristic optimization-based approach for accurate prediction and classification of knee osteoarthritis by Amal G. Diab, El-Sayed M. El-Kenawy, Nihal F. F. Areed, Hanan M. Amer, Mervat El-Seddek

“…The suggested model outperformed previous models with accuracy, sensitivity, and specificity of 0.988692, 0.980156, and 0.990089, respectively. …”
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Optimal Statistical Feature Subset Selection for Bearing Fault Detection and Severity Estimation by Chhaya Grover, Neelam Turk

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Design and Optimization for Straw Treatment Device Using Discrete Element Method (DEM) by Shaochuan Li, Peisong Diao, Xianghao Li, Yongli Zhao, Hongda Zhao

“…In this study, the Discrete Element Method (DEM) was employed to construct models of compacted soil and hollow, flexible wheat straw, forming the foundation for a comprehensive interaction model between the tool, soil, and straw. …”
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StomachNet: Optimal Deep Learning Features Fusion for Stomach Abnormalities Classification by Muhammad Attique Khan, Muhammad Shahzad Sarfraz, Majed Alhaisoni, Abdulaziz A. Albesher, Shuihua Wang, Imran Ashraf

“…A fully automated design is proposed in this work employing optimal deep learning features for classifying gastrointestinal infections. …”
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Optimizing Immunotherapy: The Synergy of Immune Checkpoint Inhibitors with Artificial Intelligence in Melanoma Treatment by Mohammad Saleem, Abigail E. Watson, Aisha Anwaar, Ahmad Omar Jasser, Nabiha Yusuf

“…Key findings highlight the efficacy of AI in improving ICI outcomes. Machine learning models successfully identified prognostic cytokine signatures linked to nivolumab clearance. …”
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Two Power Allocation and Beamforming Strategies for Active IRS-aided Wireless Network via Machine Learning by Q. Cheng, J. Bai, X. Wang, B. Shi, W. Gao, F. Shu

“…To tackle this non-convex problem, we solve this problem by alternately optimizing these variables. The PA factor is designed via polynomial regression method in machine learning. …”
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