Prediction of a Panel of Programmed Cell Death Protein-1 (PD-1) Inhibitor–Sensitive Biomarkers Using Multiphase Computed Tomography Imaging Textural Features: Retrospective Cohort... by Shiqi Wang, Na Chai, Jingji Xu, Pengfei Yu, Luguang Huang, Quan Wang, Zhifeng Zhao, Bin Yang, Jiangpeng Wei, Xiangjie Wang, Gang Ji, Minwen Zheng

“…Least absolute shrinkage and selection operator regression was applied to select key features. In total, 3 models were constructed using the Extreme Gradient Boosting algorithm: AP-only (8 features), PP-only (22 features), and a fused model combining AP and PP features (20 features: 6 AP and 14 PP features). …”
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Sensitive Multispectral Variable Screening Method and Yield Prediction Models for Sugarcane Based on Gray Relational Analysis and Correlation Analysis by Shimin Zhang, Huojuan Qin, Xiuhua Li, Muqing Zhang, Wei Yao, Xuegang Lyu, Hongtao Jiang

“…To identify yield-sensitive vegetation indices (VIs), a spectral feature selection criterion combining gray relational analysis and correlation analysis (GRD-r) was proposed. Subsequently, three supervised learning algorithms—Gradient Boosting Decision Tree (GBDT), Random Forest (RF), and Support Vector Machine (SVM)—were employed to develop both single-stage and multi-stage yield prediction models. …”
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Intelligent Data Reduction for IoT: A Context-Driven Framework by Laercio Pioli, Douglas D. J. De Macedo, Daniel G. Costa, Mario A. R. Dantas

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Predicting Patients’ Revisit Intention Based on Satisfaction Scores: Combination of Penalized Regression and Neural Networks by Farshid Abdi, Shaghayegh Abolmakarem, Amir Karbassi Yazdi, Paul Leger, Yong Tan, Giuliani Coluccio

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Machine learning-assisted early detection of keratoconus: a comparative analysis of corneal topography and biomechanical data by Arkadiusz Syta, Arkadiusz Podkowiński, Tomasz Chorągiewicz, Robert Karpiński, Jakub Gęca, Dominika Wróbel-Dudzińska, Katarzyna E Jonak, Dariusz Głuchowski, Marcin Maciejewski, Robert Rejdak, Kamil Jonak

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The value of a combined model based on ultra-radiomics and multi-modal ultrasound in the benign-malignant differentiation of C-TIRADS 4A thyroid nodules: a prospective multicenter... by Shuai Cui, Qifan Liu, Hailong Wang, Husha Li, Wei Li, Chenlong Li, Leilei Bi, Yang Mu, Wenjing Guo, Jundong Yao, Zhoulong Zhang

“…Based on the enrollment timeline, patients were divided into a training set (n=312) and a test set (n=134) in a 7:3 ratio. Using clinical information, multimodal ultrasound features, and radiomics features, a radiomics model was constructed using the Random Forest (RF) machine learning algorithm. …”
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A Review on Stable Precipitation Type Forecast in Winter by Zhao Linna, Mu Xiuxiang, Ma Cuiping, Wang Xiujuan, Li Dihua

“…., precipitation type) are crucial for decision-making and can help minimize the potential impacts. …”
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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…We tested seven different algorithms: K-Nearest Neighbors, Decision Tree, Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Logistic Regression. …”
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Machine Learning-Based Alfalfa Height Estimation Using Sentinel-2 Multispectral Imagery by Hazhir Bahrami, Karem Chokmani, Saeid Homayouni, Viacheslav I. Adamchuk, Rami Albasha, Md Saifuzzaman, Maxime Leduc

“…Three machine learning algorithms were employed to estimate plant height from satellite images: random forest (RF), support vector regression (SVR), and extreme gradient boosting (XGB). …”
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Validity of four clinical prediction scores for pulmonary embolism in a sub-Saharan African setting: a protocol for a Cameroonian multicentre cross-sectional study by Joel Noutakdie Tochie, Agnès Esiéné, Paul Owono Etoundi, Junette Arlette Mbengono Metogo, Jacqueline Ze Minkande

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OncoTrace‐TOO: Interpretable Machine Learning Framework for Cancer Tissue‐of‐Origin Identification Using Transcriptomic Signatures by Yang Hao, Haochun Huang, Daiyun Huang, Jianwen Ruan, Xin Liu, Jianquan Zhang

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Comparative effect of traditional and collaborative watershed management approaches on flood components by Ali Nasiri Khiavi, Mehdi Vafakhah, Seyed Hamidreza Sadeghi, Changhyun Jun, Sayed M. Bateni

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Data-driven prediction of rate of penetration (ROP) in drilling operations using advanced machine learning models by Guoli Huang, Sarah Kanaan Hamzah, Pinank Patel, T. Ramachandran, Aman Shankhyan, A. Karthikeyan, Dhirendra Nath Thatoi, Deepak Gupta, S. AbdulAmeer, Mariem Alwan, Zahraa Saad Abdulali, Mahmood Jasem Jawad, Hiba Mushtaq, Mohammad Mahtab Alam, Hojjat Abbasi

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Privacy guarantees for personal mobility data in humanitarian response by Nitin Kohli, Emily Aiken, Joshua E. Blumenstock

“…Specifically, we (1) introduce an algorithm for constructing differentially private mobility matrices and derive privacy and accuracy bounds on this algorithm; (2) use real-world data from mobile phone operators in Afghanistan and Rwanda to show how this algorithm can enable the use of private mobility data in two high-stakes policy decisions: pandemic response and the distribution of humanitarian aid; and (3) discuss practical decisions that need to be made when implementing this approach, such as how to optimally balance privacy and accuracy. …”
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Evaluation of LSRB Pathfinding Performance in an Autonomous Obstacle-Avoiding Robot by Usran Usran, Muh. Rafly Rasyid, Wawan Firgiawan

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Constructing network enterprise structure to create innovative products by Yu. F. Telnov, V. M. Trembach, A. V. Danilov, E. V. Yaroshenko, V. A. Kazakov, O. A. Kozlova

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Early Childhood Anemia in Ghana: Prevalence and Predictors Using Machine Learning Techniques by Maryam Siddiqa, Gulzar Shah, Mahnoor Shahid Butt, Asifa Kamal, Samuel T. Opoku

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Iron Ore Information Extraction Based on CNN-LSTM Composite Deep Learning Model by Haili Chen, Mengxiang Xia, Yaping Zhang, Ruonan Zhao, Bingran Song, Yang Bai

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A Method for Identifying Landslide-Prone Areas Using Multiple Factors and Adaptive Probability Thresholds: A Case Study in Northern Tongren, Longwu River Basin, Qinghai Province by Jiawen Bao, Xiaojun Luo, Yueling Shi, Mingyue Hou, Jichao Lv, Guoxiang Liu

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To the analysis of methods and mechanisms of predictive modeling of onboard equipment reliability when solving problems of aircraft maintenance workload planning by B. I. Ogunvoul, V. D. Budaev, D. O. Sizikov, N. V. Gorbakon, A. V. Vlasova

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