Identifying emphysema risk using brominated flame retardants exposure: a machine learning predictive model based on the SHAP methodology by Qihang Xie, Haoran Qu, Jianfeng Li, Rui Zeng, Wenhao Li, Rui Ouyang, Chengxiang Zhang, Siyu Xie, Siyu Xie, Ming Du

“…Eight machine learning algorithms, including lightGBM, MLP, DT, KNN, RF, SVM, Enet, and XGBoost, were applied to build and evaluate the model. …”
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Future of Alzheimer's detection: Advancing diagnostic accuracy through the integration of qEEG and artificial intelligence by Sahar Rezaei, Farzan Asadirad, Alireza Motamedi, Mohammadsadegh Kamran, Farzaneh Parsa, Haniyeh Samimi, Parna Ghannadikhosh, Mahdi Zahmatyar, Seyed Ali Hosseinzadeh, Hossein Arabi

“…Through systematic analysis of 11 key studies across multiple international databases, we evaluated various AI architectures, including machine learning algorithms and deep learning networks, applied to qEEG data for AD detection. …”
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HRMS-SCD:A High-Resolution Multi-Scene Satellite Imagery Dataset for Comprehensive Land-Cover Semantic Change Detection by P. Guo, P. Guo, S. Yang, H. Zhang, X. Huang, X. Ning, Y. Han, R. Zhang, M. Hao

“…Semantic change detection (SCD) focuses on identifying changes in surface coverage while simultaneously classifying the types of changes. …”
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FUSCANet: Enhancing Skin Disease Classification Through Feature Fusion and Spatial-Channel Attention Mechanisms by Qinyang Liu, Xuan Wang, Hongjiu Liu, Xiangzhen Zang, Lei Li, Zhanlin Ji, Ivan Ganchev

“…With the widespread application of computer vision technology in dermatology, automating skin lesion classification through computer algorithms has become a crucial method for improving diagnostic efficiency and reducing the mortality rate due to malignant skin conditions. …”
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Advancements in deep learning for early diagnosis of Alzheimer’s disease using multimodal neuroimaging: challenges and future directions by Muhammad Liaquat Raza, Muhammad Liaquat Raza, Muhammad Liaquat Raza, Syed Tawassul Hassan, Subia Jamil, Noorulain Hyder, Kinza Batool, Sajidah Walji, Muhammad Khizar Abbas

“…Deep learning models have also shown promise in predictive modeling, identifying potential biomarkers and forecasting disease progression.DiscussionWhile deep learning approaches show great potential, several challenges remain. …”
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Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…In all experiments, XGBoost performed best individually, while SVM was worst. The ensemble models outperformed individuals, with the GridSearchCV ensemble achieving 97.3% accuracy, an improvement exceeding the existing literature’s models by 2.3%. …”
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Mechanical Ventilation Strategies in Buildings: A Comprehensive Review of Climate Management, Indoor Air Quality, and Energy Efficiency by Farhan Lafta Rashid, Mudhar A. Al-Obaidi, Najah M. L. Al Maimuri, Arman Ameen, Ephraim Bonah Agyekum, Atef Chibani, Mohamed Kezzar

“…The findings indicate that demand-controlled ventilation (DCV) can enhance energy efficiency by up to 88% while maintaining CO₂ concentrations below 1000 ppm during 76% of the occupancy period. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…It was shown that artificial neural networks were the most common kind of trained model, while several other models were often used as benchmarks for performance. …”
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A machine learning-based methodology for short-term kinetic energy forecasting with real-time application: Nordic Power System case by Jose Miguel Riquelme-Dominguez, Manuel Carranza-García, Pedro Lara-Benítez, Francisco M. González-Longatt

“…Experimental assessment has been carried out using Typhoon HIL-404 simulator, verifying that both algorithms are suitable for real-time simulation.…”
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Health economics evaluation of diagnostic strategies for gastro-oesophageal reflux disease with reflux symptoms in China: a modelling study by Yang Chen, Feng Xie, Hongda Chen, Dong Wu, Xiaoqing Li, Xiaxiao Yan, Meiduo Ouzhu, Ziqi Guo, Chengzhen Lyu, Daiyu Yang

“…Objectives American College of Gastroenterology (ACG) and Chinese expert consensus recommended different algorithmic approaches for the diagnosis of gastro-oesophageal reflux disease (GERD) are not yet defined. …”
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Dual Control Strategy for Non-Minimum Phase Behavior Mitigation in DC-DC Boost Converters Using Finite Control Set Model Predictive Control and Proportional–Integral Controllers by Alejandra Marmol, Elyas Zamiri, Marziye Purraji, Duberney Murillo, Jairo Tuñón Díaz, Aitor Vazquez, Angel de Castro

“…The PI controller addresses small deviations in output voltage, primarily due to model prediction inaccuracies, ensuring steady-state accuracy, while the FCS-MPC handles fast dynamic responses to adapt the controller’s behavior based on load conditions. …”
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Information Metasurface Technology-enabled Integrated Passive Wireless Communication System Based on Synthetic Aperture Radar by Hua LI, Kaiyu LIU, Yunkai DENG, Zhenning LI, Chao LUO, Jichen LI, Taoyu REN, Yao CHEN, Kaijiang XU

“…However, due to significant differences between the waveform characteristics, transceiver design, and signal processing algorithms of the technologies, integrating communication and remote sensing in spaceborne systems presents numerous challenges. …”
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Unmanned Aerial Vehicle Remote Sensing for Monitoring Fractional Vegetation Cover in Creeping Plants: A Case Study of <i>Thymus mongolicus</i> Ronniger by Hao Zheng, Wentao Mi, Kaiyan Cao, Weibo Ren, Yuan Chi, Feng Yuan, Yaling Liu

“…FVC estimation models were developed using four algorithms: multiple linear regression (MLR), random forest (RF), support vector regression (SVR), and artificial neural network (ANN). …”
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Statistical Characteristics of Nighttime Medium‐Scale Traveling Ionospheric Disturbances From 10‐Years of Airglow Observation by the Machine Learning Method by Chang Lai, Jiyao Xu, Zhishuang Lin, Kun Wu, Donghe Zhang, Qinzeng Li, Longchang Sun, Wei Yuan, Yajun Zhu

“…We developed a program code using the algorithms to identify and extract the propagation and morphological features of MSTIDs in 630 nm airglow images automatically. …”
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Predicting postoperative trauma-induced coagulopathy in patients with severe injuries by machine learning by Xiaohui Du, Wei Wang, Bo Xu, Jiang Zheng, Victor W. Xia, Yi Guo, Shuai Feng, Qingxiang Mao, Hong Fu

“…Data of one hospital (n = 1204) was used for the development dataset, while other three hospitals contributed to the external validation dataset (n = 863). …”
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Development of a machine learning-derived dendritic cell signature for prognostic stratification in lung adenocarcinoma by Fang Zhou, Fang Zhou, Meng Wang, Meng Wang, Zheng Wang, Zheng Wang, Wei Li, Wei Li, Xike Lu, Xike Lu

“…A dendritic cell-related signature (DCRS) was constructed using multiple machine learning algorithms (Lasso-Cox, RSF, CoxBoost, Stepwise-Cox), and its prognostic performance was validated in seven external cohorts. …”
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Machine learning-based Diagnostic model for determining the etiology of pleural effusion using Age, ADA and LDH by Qing-Yu Chen, Shu-Min Yin, Ming-Ming Shao, Feng-Shuang Yi, Huan-Zhong Shi

“…The dataset was divided into training and test set with a ratio of 7:3 with 6 machine learning algorithms implemented to diagnosis pleural effusion. …”
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A machine-learning approach for predicting butyrate production by microbial consortia using metabolic network information by Claudia Silva-Andrade, Sergio Hernández, Pedro Saa, Ernesto Perez-Rueda, Daniel Garrido, Alberto J. Martin

“…While consortia with more than two bacteria showed generally worse predictions, the best machine-learning models still outperformed predictions from genome-scale metabolic models alone. …”
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Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs by Anwar Ahmad, Lindita Bande, Waleed Ahmed, Kheira Tabet Aoul, Mukesh Jha

“…This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. …”
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An in-depth exploration of the association between olanzapine, quetiapine and acute pancreatitis based on real-world datasets and network toxicology analysis by Shuang Wang, Liying Song, Yuanjie Sun, Haonan Zhou, Jia Yao

“…First, the reports of antipsychotics were extracted from the US FDA Adverse Event Reporting System (FAERS), and the signals of AP were detected by four pharmacovigilance algorithms. The gene targets of drugs were predicted using multiple databases. …”
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