Prognostic implications of the high sensitivity C-reactive protein to albumin ratio for major cardiovascular adverse events in patients undergoing noncardiac surgery by Yingjie Chen, Jingfang Lin, Dongxu Chen, Jundan Jiang, Yongxin Huang, Cansheng Gong, Yawen Xie, Xiaohui Chen, Ting Zheng, Yanling Tang, Xiaochun Zheng, Yanling Liao

“…The feature significance and predictive models were developed via the Boruta algorithm and machine learning techniques. …”
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The Effect of Extended Smartphone Screen Time on Continuous Partial Attention by M. Fırat

“…Students attributed this finding to hypnotic algorithms, distracting redundancy, marketing and advertising, passive receiver mode, short video flow, and surprising content. …”
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PRINCIPLES OF ANTIBIOTIC TREATMENT OF OUT-OF-HOSPITAL UPPER RESPIRATORY TRACT INFECTIONS IN CHILDREN by A. L. Zaplatnikov, N. V. Koroid, A. A. Girina, I. V. Neyman

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Enhanced flux potential analysis links changes in enzyme expression to metabolic flux by Xuhang Li, Albertha J M Walhout, L Safak Yilmaz

“…Abstract Algorithms that constrain metabolic network models with enzyme levels to predict metabolic activity assume that changes in enzyme levels are indicative of flux variations. …”
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Advancing Smart Zero-Carbon Cities: High-Resolution Wind Energy Forecasting to 36 Hours Ahead by Haytham Elmousalami, Aljawharah A. Alnaser, Felix Kin Peng Hui

“…The WSPFS leverages 12 AI algorithms both individual and ensemble models to forecast wind speed (WSF) and wind power (WPF) at intervals of 10 min to 36 h. …”
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LoRa Technology Enhanced with a Custom-Designed High-Gain Yagi-Uda Antenna for Data Transmission from Misti Volcano Monitoring to Arequipa City by Flor de Milagro Yesit Arana Medina, Jorge Rendulich

“…In response, this project integrates Internet of Things (IoT) technology, the LoRa (Long Range) network, and an optimized seven-element Yagi-Uda antenna, developed using advanced optimization algorithms to enhance transmission efficiency. The primary objective is to facilitate the reliable collection and transmission of critical sensor data for subsequent analysis by volcanological experts, thereby supporting improved prediction and mitigation of potential volcanic hazards. …”
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House Value Estimation using Different Regression Machine Learning Techniques by Tarek Ghamrawi, Müesser Nat

“…This study investigates the effectiveness of various regression algorithms in estimating house values using a dataset sourced from Zillow.com, encompassing 15,000 residential properties from Denver, Colorado. …”
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Phonon-mediated high-temperature superconductivity in clathrate superhydride ThCeH18 under pressure by Prutthipong Tsuppayakorn-aek, Wei Luo, Thiti Bovornratanaraks

“…Abstract Predicting high-temperature superconductivity in hydrogen-rich dense metallic states under pressure remains a significant challenge. …”
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Anti‐interference lithium‐ion battery intelligent perception for thermal fault detection and localization by Luyu Tian, Chaoyu Dong, Rui Wang, Yunfei Mu, Hongjie Jia

“…Therefore, a lithium‐ion battery thermal fault diagnosis model based on deep learning algorithms is presented, which includes three parts: autoencoder denoising network, coarse mask generator, and mask precise adjustment. …”
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An integrated framework for satellite-based flood mapping and socioeconomic risk analysis: A case of Thailand by Nutchapon Prasertsoong, Nattapong Puttanapong

“…The study also merges these satellite-based indices with official provincial GDP data from 2018 to 2022 to empirically analyze socioeconomic impacts using four machine learning algorithms. The result obtained from Random Forest (RF) demonstrates the highest predictive power for GDP forecasting (r-squared value of 0.912). …”
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A spatially explicit containment modelling approach for escaped wildfires in a Mediterranean climate using machine learning by Gbenga Lawrence Alawode, Pere Joan Gelabert, Marcos Rodrigues

“…Using machine learning algorithms, geospatial data, and 124 historical wildfire perimeters from 2000 to 2015, we developed a predictive model with high accuracy (Area Under the Receiver Operating Characteristics Curve = 0.81 ± 0.03) over 32,108 km2 at a 30-meter resolution. …”
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Assessing wildfire susceptibility in Iran: Leveraging machine learning for geospatial analysis of climatic and anthropogenic factors by Ehsan Masoudian, Ali Mirzaei, Hossein Bagheri

“…Utilizing advanced remote sensing, geospatial information system (GIS) processing techniques such as cloud computing, and machine learning algorithms, this research analyzed the impact of climatic parameters, topographic features, and human-related factors on wildfire susceptibility assessment and prediction in Iran. …”
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MeDML: Med-Dynamic Meta Learning - A multi-layered representation to identify provider fraud in healthcare by Nitish Kumar, Deepak Chaurasiya, Alok Singh, Siddhartha Asthana, Kushagra Agarwal, Ankur Arora

“…We test the dynamically generated meta embedding using various downstream models and show that it outperforms all baseline algorithms for provider fraud prediction task.…”
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Machine Learning-Based Classification for Crop-Type Mapping Using the Fusion of High-Resolution Satellite Imagery in a Semiarid Area by Aicha Moumni, Abderrahman Lahrouni

“…Three machine learning classifier algorithms, artificial neural network (ANN), support vector machine (SVM), and maximum likelihood (ML), were applied to identify and map crop types in irrigated perimeter. …”
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Role of Bioinformatics in Agriculture by M. N. V. Prasad Gajula, Anuj Kumar, E. A. Siddiq, A. K. Polumetla

“…Bioinformatics is the use of computer technology, mathematical algorithms, and statistics with concepts in the life sciences to solve biological problems. …”
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A Portable UV-LED/RGB Sensor for Real-Time Bacteriological Water Quality Monitoring Using ML-Based MPN Estimation by Andrés Saavedra-Ruiz, Pedro J. Resto-Irizarry

“…The novel combination of ML and MPN analysis was shown to predict in 30 min the bacterial concentration of a water sample with a minimum prediction accuracy of 84%.…”
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Graph-based two-level indicator system construction method for smart city information security risk assessment by Li Yang, Kai Zou, Yuxuan Zou

“…For the simulation of risk level prediction, we compared our method with some machine learning algorithms, such as ridge regression, Lasso regression, support vector regression, decision trees, and multi-layer perceptron. …”
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Federated Learning-Based Credit Card Fraud Detection: A Comparative Analysis of Advanced Machine Learning Models by Zheng Han

“…Because of the privacy concerns about the transaction data, it is essential not to leak it when training prediction models for credit card fraud analysis. Challenges for credit card fraud monitoring include highly imbalanced datasets and the need for advanced models to detect fraud patterns. …”
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Forecasting the volatility of Financial Time Series by Tree Ensembles by O. S. Vidmant

“…More stringent liquidity and transparency standards in relation to the financial sector also encourage participants to experiment with protective mechanisms and to create predictive algorithms that can not only reduce the losses from the volatility of financial instruments but also benefit from short-term investment manipulations. …”
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Temporal-Sequence Offline Reinforcement Learning for Transition Control of a Novel Tilt-Wing Unmanned Aerial Vehicle by Shiji Jin, Wenjie Zhao

“…Although online reinforcement learning algorithms offer adaptability, they depend on real-world exploration, posing considerable safety and cost risks for safety-critical UAV applications. …”
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