Machine learning models coupled with ionic fragment σ-profiles to predict ammonia solubility in ionic liquids by Kaikai Li, Yuesong Zhu, Sensen Shi, Yongzheng Song, Haiyan Jiang, Xiaochun Zhang, Shaojuan Zeng, Xiangping Zhang

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Phenomics assisted trait dissection and genotype selection for improved nitrogen use efficiency in rice by Nguyen Trung Duc, Dhandapani Raju, Sudhir Kumar, Renu Pandey, Ranjith Kumar Ellur, Gopala Krishnan S, Chandan Vishwakarma, Elangovan Allimuthu, Biswabiplab Singh, Ambika Rajendran, Rabi Narayan Sahoo, Viswanathan Chinnusamy

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Overview of Extension Program Planning Models by John M. Diaz, Cody Gusto, David Diehl

“…The purpose of this 6-page article is to articulate a comparative overview of the various program planning models designed and employed by Extension professionals in education contexts. …”
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Comprehensive propagation of errors for the prediction of woody biomass by Stephen H. Roxburgh, Keryn I. Paul

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Enhancing Pollen Prediction in Beijing, a Chinese Megacity: Leveraging Ensemble Learning Models for Greater Accuracy by Wenxi Ruan, Ziming Li, Zhaobin Sun, Xingqin An, Yuxin Zhao, Shuwen Zhang, Yinglin Liang, Yaqin Bu, Jingyi Xin, Xiaoyi Hang

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Research progress on evaluation and prediction of degradation in service performance for asphalt pavement by Ran Zhang, Pengkun Hu, Yuhui Zhong, Long Wen, Jie Ji, Long Liang

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Multimodal fusion model for prognostic prediction and radiotherapy response assessment in head and neck squamous cell carcinoma by Ruxian Tian, Feng Hou, Haicheng Zhang, Guohua Yu, Ping Yang, Jiaxuan Li, Ting Yuan, Xi Chen, Ying Chen, Yan Hao, Yisong Yao, Hongfei Zhao, Pengyi Yu, Han Fang, Liling Song, Anning Li, Zhonglu Liu, Huaiqing Lv, Dexin Yu, Hongxia Cheng, Ning Mao, Xicheng Song

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Predicting Heart Rate Slow Component Dynamics: A Model Across Exercise Intensities, Age, and Sex by Massimo Teso, Alessandro L. Colosio, Maura Loi, Jan Boone, Silvia Pogliaghi

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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

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ELM2.1-XGBfire1.0: improving wildfire prediction by integrating a machine learning fire model in a land surface model by Y. Liu, H. Huang, S.-C. Wang, T. Zhang, D. Xu, Y. Chen

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A comparison of modeling approaches for static and dynamic prediction of central-line bloodstream infections using electronic health records (part 1): regression models by Shan Gao, Elena Albu, Hein Putter, Pieter Stijnen, Frank E Rademakers, Veerle Cossey, Yves Debaveye, Christel Janssens, Ben Van Calster, Laure Wynants

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Prediction model of in-hospital mortality risk in intensive care unit patients with cardiac arrest: a multicenter retrospective cohort study based on an ensemble model by Li Liu, Wei-Wei Lai, Bo-Wen Li, Shu-Hang Wang, Mu-Ming Yu, Yan-Cun Liu, Yan-Fen Chai

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Exploring alternate coupling inputs of a data-driven model for optimum daily streamflow prediction in calibrated SWAT-BiLSTM rainfall-runoff modeling by Khalil Ahmad, Khalil Ahmad, Mudassar Iqbal, Muhammad Atiq Ur Rehman Tariq, Afed Ullah Khan, Abdullah Nadeem, Jinlei Chen, Kseniia Usanova, Kseniia Usanova, Hamad Almujibah, Hashem Alyami, Muhammad Abid

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Predicting Cardiovascular Aging Risk Based on Clinical Data Through the Integration of Mathematical Modeling and Machine Learning by Kuat Abzaliyev, Madina Suleimenova, Siming Chen, Madina Mansurova, Symbat Abzaliyeva, Ainur Manapova, Almagul Kurmanova, Akbota Bugibayeva, Diana Sundetova, Raushan Bitemirova, Nazipa Baizhigitova, Merey Abdykassymova, Ulzhas Sagalbayeva

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Evaluation of a Machine Learning Model Based on Laboratory Parameters for the Prediction of Influenza A and B in Chongqing, China: Multicenter Model Development and Validation Stud... by Weiwei Hu, Yulong Liu, Jian Dong, Xuelian Peng, Chunyan Yang, Honglin Wang, Yong Chen, Shan Shi, Jin Li

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Enhancing heart disease prediction accuracy by comparing classification models employing varied feature selection techniques by Balliu Lorena, Zanaj Blerina, Basha Gledis, Zanaj Elma, Meçe Elinda Kajo

“…It includes the analysis of different algorithms such as Decision Tree, Logistic Regression, Support Vector Machine, Random Forest and hybrid models. This results in SVM and RM performing better after applying feature selection for individual ML models. …”
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PHYSICS-DRIVEN FEATURE CREATION TO IMPROVE MACHINE LEARNING MODELS PERFORMANCE FOR OIL PRODUCTION RATE PREDICTION by Eghbal Motaei, Seyed Mehdi Tabatabai, Tarek Ganat, Ahmad Khanifar, Sulaiman Dzaiy, Timur Chis

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A Look at How Philosophical Perspectives of Adult Education Shape the Practice at Universidad Nacional, Costa Rica by Lena Barrantes-Elizondo

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Multi‑omics identification of a novel signature for serous ovarian carcinoma in the context of 3P medicine and based on twelve programmed cell death patterns: a multi-cohort machin... by Lele Ye, Chunhao Long, Binbing Xu, Xuyang Yao, Jiaye Yu, Yunhui Luo, Yuan Xu, Zhuofeng Jiang, Zekai Nian, Yawen Zheng, Yaoyao Cai, Xiangyang Xue, Gangqiang Guo

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A New Approach to Improve Accuracy of Grey Model GMC(1,n) in Time Series Prediction by Sompop Moonchai, Wanwisa Rakpuang

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