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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Bioinformatics-based analysis of nicotinamide adenine dinucleotide metabolism-related genes to predict immune status and prognosis for head and neck squamous cell carcinoma patient... by Zhenjie Guan, Xinyu Gu, Lian Zheng

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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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What Should We Know to Predict Geomagnetically Induced Currents in Power Transmission Lines? by Pilipenko Vyacheslav, Kozyreva Olga, Belahovskiy Vladimir, Sakharov Yaroslav, Selivanov Vasiliy

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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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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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Optimization of purchasing plans based on forecasted demand for resources by Szymon Niewiadomski, Grzegorz Mzyk

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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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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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Performance Enhancement of a Grid Connected Wind Turbine-Based PMSG Using Effective Predictive Control Algorithm by Mahmoud A. Mossa, Rasha A. Mohamed, Ameena Saad Al-Sumaiti

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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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Graph theoretic and machine learning approaches in molecular property prediction of bladder cancer therapeutics by Huiling Qin, Atef F. Hashem, Muhammad Farhan Hanif, Osman Abubakar Fiidow

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Machine Learning‐Based Failure Prediction in Concrete Slabs and Cubes Under Impact Loading by Mohammad Hematibahar, Ahmed Deifalla, Adham E. Ragab, Gebre Tesfaldet

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Using genomic data and machine learning to predict antibiotic resistance: A tutorial paper. by Faye Orcales, Lucy Moctezuma Tan, Meris Johnson-Hagler, John Matthew Suntay, Jameel Ali, Kristiene Recto, Phelan Glenn, Pleuni Pennings

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