Identification of Major Bleeding Events in Postoperative Patients With Malignant Tumors in Chinese Electronic Medical Records: Algorithm Development and Validation by Hui Li, Haiyang Yao, Yuxiang Gao, Hang Luo, Changbin Cai, Zhou Zhou, Muhan Yuan, Wei Jiang

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Grassland biome fragmentation analysis using sentinal-2 images and support vector machine learning model in South Africa by Andisani Netsianda, Paidamwoyo Mhangara, Eskinder Gidey

“…Given the paucity of research on the threatened ecosystem, the support vector machine learning algorithm (SVM) is employed to investigate fragmentation from 2016 to 2023. …”
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Advancements in cyberthreat intelligence through resource exhaustion attack detection using hybrid deep learning with heuristic search algorithms by S. Jayanthi, Swathi Sowmya Bavirthi, P. Murali, K. Vijaya Kumar, Hend Khalid Alkahtani, Mohamad Khairi Ishak, Samih M. Mostafa

“…Abstract The Distributed Denial of Service (DDoS) attack is uncontrollable and appears in different patterns and shapes; accordingly, it is not easily detected and solved with preceding solutions. …”
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Green cover change detection using a modified adaptive ensemble of extreme learning machines for North-Western India by Madhu Khurana, Vikas Saxena

“…It has already started affecting the weather patterns leading to disruption of normal life. Detecting change helps to monitor and plan the Earth’s resources in an efficient manner. …”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy by Xuan Zhao, Weiyun Tang, Qiuyan Liu, Hongtao Cao, Fei Chen

“…Static features, including farmland distribution and soil types, are extracted using Convolutional Neural Networks, while temporal trends in variables such as weather patterns and policy changes are captured by the Long Short-Term Memory network. …”
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Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

“…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023) by Jian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song, Wen-hua Xiong

“…The most notable research hotspots currently are the optimal selection of neural imaging markers and the most suitable machine learning algorithm models.…”
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Predictive Archaeological Risk Assessment at Reservoirs with Multitemporal LiDAR and Machine Learning (XGBoost): The Case of Valdecañas Reservoir (Spain) by Enrique Cerrillo-Cuenca, Primitiva Bueno-Ramírez

“…This study assesses the potential of using multitemporal LiDAR data and Machine Learning (ML)—specifically the XGBoost algorithm—to predict erosional and sedimentary processes affecting archaeological sites in the Valdecañas Reservoir (Spain). …”
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Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…Given the complex, non-linear patterns in solubility behavior, three advanced regression approaches were utilized: Polynomial Curve Fitting, a Bayesian-based Neural Network (BNN), and the Neural Oblivious Decision Ensemble (NODE) method. …”
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Multi-Dimensional AE Signal Features in Eccentrically Loaded Concrete Structures: A Machine Learning Classification for Damage Progression by Shilong Ding, Alipujiang Jierula, Abudusaimaiti Kali, Tong Han, Tae-Min Oh

“…The integrated approach of clustering and random forest modeling demonstrates robust feasibility in identifying AE signal patterns associated with specific damage stages, achieving an 85% recognition rate for damage stage classification. …”
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Hybrid feature selection for real-time road surface classification on low-end hardware: A machine learning approach by Cong Ngo Van, Duc-Nghia Tran, Ton That Long, Nguyen Gia Minh Thao, Duc-Tan Tran

“…Vibration-based methods have proven effective in this field, utilizing vehicle vibration patterns to determine road surface conditions. One of the challenges in this field is using optimal datasets and classification models that meet real-time applications on low-end hardware devices. …”
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Machine learning approach for identifying and forecasting streamflow droughts in data limited basins of South Korea using threshold levels by Young-Ho Seo, Jang Hyun Sung, Byung-Sik Kim, Junehyeong Park

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A Deep Learning Model Leveraging Time-Series System Call Data to Detect Malware Attacks in Virtual Machines by A. Alfred Raja Melvin, Jaspher W. Kathrine, Andrew Jeyabose, D. Cenitta

“…The raw VMM system call traces are transformed into novel Time Series System Call patterns and utilized by a deep learning algorithm for training and building the classifier model. …”
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Analisis Visual dan Machine Learning untuk Mengukur Validitas Dokumen Akademik Perpustakaan: Studi pada Data Turnitin by Hesti Ari Wardani, Imam Yuadi

“…Using a data visualization approach and machine learning algorithms, this research explores the relationship between Turnitin scores and document validity status. …”
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Adaptive AI-enhanced computation offloading with machine learning for QoE optimization and energy-efficient mobile edge systems by Dinesh Kumar Nishad, Vandna Rani Verma, Pushkar Rajput, Sandeep Gupta, Anurag Dwivedi, Dharti Raj Shah

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Integration of machine learning and bulk sequencing revealed exosome-related gene FOSB was involved in the progression of abdominal aortic aneurysm by Xianlu Ma, Xianlu Ma, Hongjie Zhou, Hongjie Zhou, Ren Wang, Ren Wang

“…The CIBERSORT algorithm was utilized to analyze the correlation between these genes and immune cell infiltration. …”
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Deterministic Light Detection and Ranging (LiDAR)-Based Obstacle Detection in Railways Using Data Fusion by Susana Dias, Pedro J. S. C. P. Sousa, João Nunes, Francisco Afonso, Nuno Viriato, Paulo J. Tavares, Pedro M. G. P. Moreira

“…Using a data fusion approach, pre-existing knowledge about the track topography is incorporated into the LiDAR data processing pipeline in conjunction with the DBSCAN clustering algorithm to identify and classify potential obstacles based on point cloud density patterns. …”
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Integration of machine learning and experimental validation to identify the prognostic signature related to diverse programmed cell deaths in breast cancer by Longpeng Li, Longpeng Li, Jinfeng Zhao, Yaxin Wang, Zhibin Zhang, Wanquan Chen, Jirui Wang, Yue Cai

“…The prognostic signature (PCDRS) were constructed by the best combination of 101 machine learning algorithm combinations, and the C-index of PCDRS was compared with 30 published signatures. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…Th1/Th2 cytokines were collected at BSI onset, with LASSO regression and restricted cubic spline analysis used to refine predictors. Seven machine learning(ML) algorithm (XGBoost, Logistic Regression, LightGBM, RandomForest, AdaBoost, GBDT and GNB) were trained using 10-fold cross-validation and model performance was evaluated with the ROC, calibration plots, decision and learning curves and the Shapley Additive Explanations (SHAP) analysis. …”
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Le profil : une rhétorique dispositive by Louise Merzeau

“…More than a self-image, the digital ethos is based on a conversational system powered by an algorithmic processing of metadata. On the one hand, the machines capture the patterns of Internet users. …”
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