Predicting the Matching Possibility of Online Dating Youths Using Novel Machine Learning Algorithm by Karthikeyan Palanisamy, Muthumani Muralidharan

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Econometric Modeling Combining MCMC Algorithm and Random Coefficient Quantile AR Model by Ting Wang

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Predicting the diversity of photosynthetic light-harvesting using thermodynamics and machine learning. by Callum Gray, Samir Chitnavis, Tamara Buja, Christopher D P Duffy

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Persistent Oscillations in the Decadal Prediction of Central Mediterranean Wetting and Drying Phases by Nazzareno Diodato, Rajib Maity, Gianni Bellocchi

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Prediction of air temperature and humidity in greenhouses via artificial neural network. by Caixia Yan, Ta Na, Qi Zhen, Yunfeng Sun, Kunyu Liu

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Prediction of Steering Angle in Autonomous Vehicles Using Deep Learning Approach by Karemore Yogesh, Dronkar Swati

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How to predict effective drug combinations – moving beyond synergy scores by Lea Eckhart, Kerstin Lenhof, Lutz Herrmann, Lisa-Marie Rolli, Hans-Peter Lenhof

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Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

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Machine learning-based prediction of soil organic matter via smartphone by Qingying Gao, Yi Chen, Hui Zhang, Jingjing Chen, Liang Wang

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Refined predictions for Starobinsky inflation and post-inflationary constraints in light of ACT by Manuel Drees, Yong Xu

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Nomogram for predicting the severity of high-risk plaques in acute coronary syndrome by Miao-Na Bai, Miao-Na Bai, Miao-Na Bai, Ji-Xiang Wang, Ji-Xiang Wang, Xiao-Wei Li, Xiao-Wei Li, Xiao-Wei Li, Jing-Xian Wang, Jing-Xian Wang, Yu-Hang Wang, Yu-Hang Wang, Yin Liu, Yin Liu, Yin Liu, Jing Gao, Jing Gao, Jing Gao, Jing Gao

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COMPARISON IN PREDICTING THE SHORT-TERM USING THE SARIMA, DSARIMA AND TSARIMA METHODS by Muhammad Giovani, Indira Anggriani, Syalam Ali Wira Dinata Simatupang

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PREDICTING THE PROBABILITY OF THE STERNAL WOUND INFECTION IN PATIENTS UNDERGOING CARDIAC SURGERY by G. G. Khubulava, N. N. Shikhverdiev, P. R. Vogt, S. P. Marchenko, V. V. Suvorov

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Predicting forest understory habitat for Canada lynx using LIDAR data by Patrick A. Fekety, Rema B. Sadak, Joel D. Sauder, Andrew T. Hudak, Michael J. Falkowski

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Predicting wildlife corridors for multiple species in an East African ungulate community. by Jason Riggio, Katie Foreman, Ethan Freedman, Becky Gottlieb, David Hendler, Danielle Radomille, Ryan Rodriguez, Thomas Yamashita, John Kioko, Christian Kiffner

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A novel RNN architecture to improve the precision of ship trajectory predictions by Martha Dais Ferreira, Jessica N. A. Campbell

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Application of Protein Structure Encodings and Sequence Embeddings for Transporter Substrate Prediction by Andreas Denger, Volkhard Helms

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Age Prediction from Facial Images Using Deep Learning Architecture by Nguyen Hai Thanh, Pham Linh Thuy Thi, Dang Dung Thi, Huynh Son Nguyen, Dang Phu Hao, Nguyen Quoc Thien Huynh

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Deep learning and pathomics analyses predict prognosis of high-grade gliomas by Yuchen Zhu, Yuchen Zhu, Yuxi Gong, Weilin Xu, Xingjian Sun, Xingjian Sun, Gefei Jiang, Gefei Jiang, Lei Qiu, Lei Qiu, Kexin Shi, Kexin Shi, Mengxing Wu, Mengxing Wu, Yinjiao Fei, Jinling Yuan, Jinling Yuan, Jinyan Luo, Yurong Li, Yuandong Cao, Minhong Pan, Shu Zhou

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A NEW METHOD FOR PREDICTING SURVIVAL AND ESTIMATING UNCERTAINTY IN TRAUMA PATIENTS by V. G. Schetinin, L. I. Jakaite, V. F. Kuriakin, V. I. Gorbachenko

“…The Trauma and Injury Severity Score (TRISS) is the current “gold” standard of screening patient’s condition for purposes of predicting survival probability. More than 40 years of TRISS practice revealed a number of problems, particularly, 1) unexplained fluctuation of predicted values caused by aggregation of screening tests, and 2) low accuracy of uncertainty intervals estimations. …”
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