A novel model for predicting immunotherapy response and prognosis in NSCLC patients by Ting Zang, Xiaorong Luo, Yangyu Mo, Jietao Lin, Weiguo Lu, Zhiling Li, Yingchun Zhou, Shulin Chen

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Developing and validating machine learning models to predict next-day extubation by Samuel W. Fenske, Alec Peltekian, Mengjia Kang, Nikolay S. Markov, Mengou Zhu, Kevin Grudzinski, Melissa J. Bak, Anna Pawlowski, Vishu Gupta, Yuwei Mao, Stanislav Bratchikov, Thomas Stoeger, Luke V. Rasmussen, Alok N. Choudhary, Alexander V. Misharin, Benjamin D. Singer, G. R. Scott Budinger, Richard G. Wunderink, Ankit Agrawal, Catherine A. Gao, NU SCRIPT Study Investigators

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Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

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Prognostic predictions in psychosis: exploring the complementary role of machine learning models by Metten Somers, Hugo G Schnack, Rene S Kahn, Diane F van Rappard, Frank L Gerritse, Edwin van Dellen, Violet van Dee, Seyed M Kia, Caterina Fregosi, Wilma E Swildens, Anne Alkema, Albert Batalla, Coen van den Berg, Danko Coric, Lotte G Dijkstra, Arthur van den Doel, Livia S Dominicus, John Enterman, Marte Z van der Horst, Fedor van Houwelingen, Charlotte S Koch, Lisanne E M Koomen, Marjan Kromkamp, Michelle Lancee, Brian E Mouthaan, Eline J Regeer, Raymond W J Salet, Jorgen Straalman, Marjolein H T de Vette, Judith Voogt, Inge Winter-van Rossum, Wiepke Cahn

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The reporting quality and methodological quality of dynamic prediction models for cancer prognosis by Peijing Yan, Zhengxing Xu, Xu Hui, Xiajing Chu, Yizhuo Chen, Chao Yang, Shixi Xu, Huijie Cui, Li Zhang, Wenqiang Zhang, Liqun Wang, Yanqiu Zou, Yan Ren, Jiaqiang Liao, Qin Zhang, Kehu Yang, Ling Zhang, Yunjie Liu, Jiayuan Li, Chunxia Yang, Yuqin Yao, Zhenmi Liu, Xia Jiang, Ben Zhang

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Expression‐based machine learning models for predicting plant tissue identity by Sourabh Palande, Jeremy Arsenault, Patricia Basurto‐Lozada, Andrew Bleich, Brianna N. I. Brown, Sophia F. Buysse, Noelle A. Connors, Sikta Das Adhikari, Kara C. Dobson, Francisco Xavier Guerra‐Castillo, Maria F. Guerrero‐Carrillo, Sophia Harlow, Héctor Herrera‐Orozco, Asia T. Hightower, Paulo Izquierdo, MacKenzie Jacobs, Nicholas A. Johnson, Wendy Leuenberger, Alessandro Lopez‐Hernandez, Alicia Luckie‐Duque, Camila Martínez‐Avila, Eddy J. Mendoza‐Galindo, David Cruz Plancarte, Jenny M. Schuster, Harry Shomer, Sidney C. Sitar, Anne K. Steensma, Joanne Elise Thomson, Damián Villaseñor‐Amador, Robin Waterman, Brandon M. Webster, Madison Whyte, Sofía Zorilla‐Azcué, Beronda L. Montgomery, Aman Y. Husbands, Arjun Krishnan, Sarah Percival, Elizabeth Munch, Robert VanBuren, Daniel H. Chitwood, Alejandra Rougon‐Cardoso

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The TB27 Transcriptomic Model for Predicting Mycobacterium tuberculosis Culture Conversion by Maja Reimann, Korkut Avsar, Andrew DiNardo, Torsten Goldmann, Gunar Günther, Michael Hoelscher, Elmira Ibraim, Barbara Kalsdorf, Stefan Kaufmann, Niklas Köhler, Anna Mandalakas, Florian Maurer, Marius Müller, Dörte Nitschkowski, Ioana Olaru, Cristina Popa, Andrea Rachow, Thierry Rolling, Helmut Salzer, Patricia Sanchez-Carballo, Maren Schuhmann, Dagmar Schaub, Victor Spinu, Elena Terhalle, Markus Unnewehr, Nika Zielinski, Jan Heyckendorf, Christoph Lange

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A Neural Network-Based Model Predictive Control for a Grid-Connected Photovoltaic–Battery System with Vehicle-to-Grid and Grid-to-Vehicle Operations by Ossama Dankar, Mohamad Tarnini, Abdallah El Ghaly, Nazih Moubayed, Khaled Chahine

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DeepPredict: a state-of-the-art web server for protein secondary structure and relative solvent accessibility prediction by Wafa Alanazi, Wafa Alanazi, Di Meng, Gianluca Pollastri

“…DeepPredict is a freely accessible web server that integrates Porter6 and PaleAle6, two state-of-the-art deep learning models designed for protein secondary structure prediction (PSSP) and relative solvent accessibility (RSA) prediction, respectively. …”
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Establishment and internal validation of a model to predict the efficacy of Adalimumab in Crohn’s disease by Fang Wang, He Zhou, Yujie Zhang, Yu Da, Tiantian Zhang, Yanting Shi, Tong Wu, Jie Liang

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Bayesian Architecture for Predictive Monitoring of Unbalance Faults in a Turbine Rotor–Bearing System by Banalata Bera, Shyh-Chin Huang, Po Ting Lin, Yu-Jen Chiu, Jin-Wei Liang

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A preliminary nomogram model for predicting relapse of patients with primary membranous nephropathy by Min Li, Huifang Wang, Xiaoying Lai, Dandan Guo, Chunhui Jiang, Zixuan Fu, Xuemei Liu

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Risk factors for early diagnosis and prediction model development of of neonatal ABO-HDFN by ZHANG Wenhua, LIU Dan, ZHANG Wenting, LING Jing

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Construction and verification of a risk factor prediction model for neonatal severe pneumonia by Weihua Gong, Kaijie Gao, Jiajia Ni, Ying Shi, Zhiming Shan, Hongqi Sun, Shanshan Wang, Jiangtao Xu, Junmei Yang

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Degradation of poly (2-ethyl-2-oxazoline) prepared at lower temperature: a study of kinetics using thermal analysis and advanced predictive modeling by Abdulrahman Alarabi, Imtiaz Ali

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Mud Loss Analysis Through Predictive Modeling of Pore Pressure and Fracture Gradients in Tin Fouye Tabankort Field, Western Illizi Basin, Algeria by Reda Laouini, Messaoud Hacini, Hocine Merabti, Fethi Medjani, Omar Mahmoud

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Development and validation of a risk assessment model for predicting the failure of early medical abortions: A clinical prediction model study based on a systematic review and meta... by An-Hao Liu, Bin Xu, Xiu-Wen Li, Yue-Wen Yu, Hui-Xin Guan, Xiao-Lu Sun, Yan-Zhen Lin, Li-Li Zhang, Xian-Di Zhuo, Jia Li, Wen-Qun Chen, Wen-Feng Hu, Ming-Zhu Ye, Xiu-Min Huang, Xun Chen

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Predictive Model for Erosion Rate of Concrete Under Wind Gravel Flow Based on K-Fold Cross-Validation Combined with Support Vector Machine by Yanhua Zhao, Kai Zhang, Aojun Guo, Fukang Hao, Jie Ma

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Cloud-Integrated Meteorological Parameter Prediction by Leveraging Multivariate Statistical Time Series and GANs by Archana Rout, Biswa Ranjan Senapati, Debahuti Mishra

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Predictive maintenance in naval vessel propulsion systems for enhanced marine operations using a BiGMM-HMM framework with divergence-based clustering by Farshid Javadnejad, Hyoshin John Park, Samuel Kovacic, Andres Sousa-Poza

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