Urinary metabolite model to predict the dying process in lung cancer patients by Séamus Coyle, Elinor Chapman, David M. Hughes, James Baker, Rachael Slater, Andrew S. Davison, Brendan P. Norman, Ivayla Roberts, Amara C. Nwosu, James A. Gallagher, Lakshminarayan R. Ranganath, Mark T. Boyd, Catriona R. Mayland, Douglas B. Kell, Stephen Mason, John Ellershaw, Chris Probert

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Machine learning model to predict sepsis in ICU patients with intracerebral hemorrhage by Lei Tang, Ye Li, Ji Zhang, Feng Zhang, Qiaoling Tang, Xiangbin Zhang, Sai Wang, Yupeng Zhang, Siyuan Ma, Ran Liu, Lei Chen, Junyi Ma, Xuelun Zou, Tianxing Yao, Rongmei Tang, Huifang Zhou, Lianxu Wu, Yexiang Yi, Yi Zeng, Duolao Wang, Le Zhang

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Mortality risk prediction model in AIDS patients with pneumocystis pneumonia in China by Xi Wang, Letian Liu, Wen Wang, Yang Zhang, Hui Chen, Zhangli Wang, Jianwei Li, Yue Gao, Yanqun Huang, Lijun Sun, Tong Zhang, Aixin Li

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Construction and validation of a presenteeism prediction model for ICU nurses in China by Jijun Wu, Yuxin Li, Yuxin Li, Xiaoli Liu, Yuting Fan, Ping Dai, Baixia Chen, Zhenfan Liu, Xian Rong, Xiaoli Zhong

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Construction of a prediction model for sarcopenic obesity based on machine learning by Mengru Xu, Mengru Xu, Jia Liu, Jia Liu, Song Hu, Song Hu, Tongxiao Luan, Tongxiao Luan, Yuting Duan, Yuting Duan, Aohua Wang, Aohua Wang, Ziwei Cui, Ziwei Cui, Jing Zhou, Yongjun Mao, Yongjun Mao

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Prediction of the monthly river water level by using ensemble decomposition modeling by Chaitanya Baliram Pande, Lariyah Mohd Sidek, Bijay Halder, Okan Mert Katipoğlu, Jitendra Rajput, Fahad Alshehri, Rabin Chakrabortty, Subodh Chandra Pal, Norlida Mohd Dom, Miklas Scholz

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Development and validation of a Prediction Model for Chronic Thromboembolic Pulmonary Disease by Guixiang Liu, Jing Wen, Chunyi Lv, Mingjie Liu, Min Li, Kexia Fang, Jianwen Fei, Nannan Zhang, Xuehua Li, Huarui Wang, Yuanyuan Sun, Ling Zhu

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Machine learning model for random forest acute oral toxicity prediction by A.M. Elsayad, M.M. Zeghid, K.A. Elsayad, A.N. Khan, ِA.K.M. Baareh, A. Sadiq, S.A. Mukhtar, H.F. Ali, S. Abd El-kader

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The clinical prediction model to distinguish between colonization and infection by Klebsiella pneumoniae by Xiaoyu Zhang, Xifan Zhang, Deng Zhang, Jing Xu, Jingping Zhang, Xin Zhang

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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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A Brief Overview of Modeling Estimation of State of Health for an Electric Vehicle’s Li-Ion Batteries by Ehab H. E. Bayoumi, Michele De Santis, Hilmy Awad

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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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Neural network forecasting of energy generation by solar panels by S. M. Stepanov, N. A. Iskra

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Do Learning Activities Improve Students' Ability to Construct Explanatory Models with a Prism Foil Problem? by Mihael Gojkošek, Josip Sliško, Gorazd Planinšič

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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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