Joint Prediction of U.S. Rice Yields and Methane Emissions: A Machine Learning Approach by Jameson Augustin, Munisamy Gopinath, Berna Karali, Yuhan Rao

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On Usage of Artificial Intelligence for Predicting Neonatal Diseases, Conditions, and Mortality: A Bibliometric Review by Flavio Leandro de Morais, Raysa Carla Leal da Silva, Anna Beatriz Silva, Estefani Pontes Simao, Maria Eduarda Ferro de Mello, Stephany Paula da Silva Canejo, Katia Maria Mendes, Waldemar Brandao Neto, Jackson Raniel Florencio da Silva, Maicon Herverton Lino Ferreira da Silva Barros, Patricia Takako Endo

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Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach by Isha Gupta, Anu Bajaj, Manav Malhotra, Vikas Sharma, Ajith Abraham

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Use of childhood adversity and mental health admission patterns to predict suicide in young people by Anna Tarasenko, Dennis Ougrin

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Development and validation of survival prediction tools in early and late onset colorectal cancer patients by Wanling Li, Jinshan Liu, Yuntong Lan, Dongling Yu, Bingqiang Zhang

“…Abstract This study aims to develop online calculators using machine learning models to predict survival probabilities for early- and late-onset colorectal cancer (EOCRC and LOCRC) over a 1- to 8-year period. …”
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Analysis of the Full Spitzer Microlensing Sample. I. Dark Remnant Candidates and Gaia Predictions by Krzysztof A. Rybicki, Yossi Shvartzvald, Jennifer C. Yee, Sebastiano Calchi Novati, Eran O. Ofek, Ian A. Bond, Charles Beichman, Geoff Bryden, Sean Carey, Calen Henderson, Wei Zhu, Michael M. Fausnaugh, Benjamin Wibking, The Spitzer Team, Andrzej Udalski, Radek Poleski, Przemek Mróz, Michał K. Szymański, Igor Soszyński, Paweł Pietrukowicz, Szymon Kozłowski, Jan Skowron, Krzysztof Ulaczyk, Patryk Iwanek, Marcin Wrona, The OGLE Collaboration, Yoon-Hyun Ryu, Michael D. Albrow, Sun-Ju Chung, Andrew Gould, Cheongho Han, Kyu-Ha Hwang, Youn Kil Jung, In-Gu Shin, Hongjing Yang, Weicheng Zang, Sang-Mok Cha, Dong-Jin Kim, Hyoun-Woo Kim, Seung-Lee Kim, Chung-Uk Lee, Dong-Joo Lee, Yongseok Lee, Byeong-Gon Park, Richard W. Pogge, The KMTNet Collaboration, Fumio Abe, Richard Barry, David P. Bennett, Aparna Bhattacharya, Akihiko Fukui, Ryusei Hamada, Shunya Hamada, Naoto Hamasaki, Yuki Hirao, Stela Ishitani Silva, Yoshitaka Itow, Rintaro Kirikawa, Naoki Koshimoto, Yutaka Matsubara, Shota Miyazaki, Yasushi Muraki, Tutumi Nagai, Kansuke Nunota, Greg Olmschenk, Clement Ranc, Nicholas J. Rattenbury, Yuki K. Satoh, Takahiro Sumi, Daisuke Suzuki, Paul. J. Tristram, Aikaterini Vandorou, Hibiki Yama, MOA collaboration, Łukasz Wyrzykowski, Kornel Howil, Katarzyna Kruszyńska

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Integrating pollinators’ movements into pollination models by Juliane Mailly, Louise Riotte-Lambert, Mathieu Lihoreau

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Uncertainty quantification in tree structure and polynomial regression algorithms toward material indices prediction by Geng-Fu He, Pin Zhang, Zhen-Yu Yin

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Closed-Loop Clustering-Based Global Bandwidth Prediction in Real-Time Video Streaming by Sepideh Afshar, Reza Razavi, Mohammad Moshirpour

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Random fields and up scaling, towards a more predictive probabilistic quantitative hydrogeology by Noetinger, Benoît

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Predicting Individualized Joint Kinematics Over Continuous Variations of Walking, Running, and Stair Climbing by Emma Reznick, Cara Gonzalez Welker, Robert D. Gregg

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Continuous Speech-Based Fatigue Detection and Transition State Prediction for Air Traffic Controllers by Susmitha Vekkot, Surya Teja Chavali, Charan Tej Kandavalli, Rama Sai Abhishek Podila, Deepa Gupta, Mohammed Zakariah, Yousef Ajami Alotaibi

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An Integrated Method for High-Dimensional Imbalanced Assembly Quality Prediction Supported by Edge Computing by Yixiong Feng, Tianyue Wang, Bingtao Hu, Chen Yang, Jianrong Tan

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Graph-Based Prediction of Spatio-Temporal Vaccine Hesitancy From Insurance Claims Data by Sifat Afroj Moon, Rituparna Datta, Tanvir Ferdousi, Hannah Baek, Abhijin Adiga, Achla Marathe, Anil Vullikanti

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Arctic tern-optimized weighted feature regression system for predicting bridge scour depth by Jui-Sheng Chou, Asmare Molla

“…This paper presents a pioneering artificial intelligence (AI) solution – the Arctic Tern-Optimized Weighted Feature Least Squares Support Vector Regression (ATO-WFLSSVR) system to aid civil engineers in accurately predicting scour depth at bridges. This prediction system amalgamates the strengths of hybrid models by uniting a metaheuristic optimization algorithm with weighted features and least squares support vector regression (WFLSSVR). …”
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A Blending Ensemble Approach to Predicting Student Dropout in Massive Open Online Courses (MOOCs) by Muhammad Ricky Perdana Putra, Ema Utami

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Understanding the Role of the North Pacific Victoria Mode in ENSO Predictability Based on the NMME Hindcasts by Zhengyi Ren, Zongrong Li, Ruiqiang Ding, Jiangyu Mao

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PREDICTING ECONOMIC BEHAVIOR BASED ON ECONOMICS EDUCATION IN THE FAMILY AND UNIVERSITY BY MEDIATING ECONOMIC LITERACY by farideh nasiri, sakineh jafari

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Data-intelligence driven methods for durability, damage diagnosis and performance prediction of concrete structures by Fan Li, Daming Luo, Ditao Niu

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Applying a transformer architecture to intraoperative temporal dynamics improves the prediction of postoperative delirium by Niklas Giesa, Maria Sekutowicz, Kerstin Rubarth, Claudia Doris Spies, Felix Balzer, Stefan Haufe, Sebastian Daniel Boie

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