Correcting errors in seasonal Arctic sea ice prediction of Earth system models with machine learning by Z. He, Z. He, Z. He, Y. Wang, J. Brajard, X. Wang, X. Wang, Z. Shen, Z. Shen

“…In this study, we integrate a multilayer perceptron (MLP) machine learning (ML) model into the Norwegian Climate Prediction Model (NorCPM) to improve seasonal sea ice predictions. …”
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Winter Wheat Yield Prediction Using Satellite Remote Sensing Data and Deep Learning Models by Hongkun Fu, Jian Lu, Jian Li, Wenlong Zou, Xuhui Tang, Xiangyu Ning, Yue Sun

Subjects: “…wheat yield prediction…”
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Metamorphic Facies Distribution in the Western Alps Predicted by Petrological‐Thermomechanical Models of Syn‐Convergent Exhumation by Joshua D. Vaughan‐Hammon, Lorenzo G. Candioti, Thibault Duretz, Stefan M. Schmalholz

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Improving Temperature Prediction Precision for Aerial Cameras by Correcting Structure and Parameters of Thermal Network Models by Yue Fan, Wei Feng, Zhenxing Ren, Bingqi Liu, Jinying Li

“…This paper introduces a methodology for improving the precision of temperature predictions generated by thermal network models for aerial cameras, which involves correcting the structure and parameters of the thermal network. …”
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Reporting of Fairness Metrics in Clinical Risk Prediction Models Used for Precision Health: Scoping Review by Lillian Rountree, Yi-Ting Lin, Chuyu Liu, Maxwell Salvatore, Andrew Admon, Brahmajee Nallamothu, Karandeep Singh, Anirban Basu, Fan Bu, Bhramar Mukherjee

“…ObjectiveWe seek to assess the uptake of fairness metrics in clinical risk prediction modeling through an empirical evaluation of popular prediction models for 2 diseases, 1 chronic and 1 infectious disease. …”
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Leveraging large language models to predict antibody biological activity against influenza A hemagglutinin by Ella Barkan, Ibrahim Siddiqui, Kevin J. Cheng, Alex Golts, Yoel Shoshan, Jeffrey K. Weber, Yailin Campos Mota, Michal Ozery-Flato, Giuseppe A. Sautto

“…We explore an AI model for predicting the binding and receptor blocking activity of antibodies against influenza A hemagglutinin (HA) antigens. …”
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Comparison of the prediction effects of LSTM, SARIMA and SARIMAX models on the incidence of hand, foot, and mouth disease by ZHANG Xiaoqiao, ZHANG Xiaodie, ZHAO Zhenxi, XIE Pengliu, DAI Min

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Prediction Models for Perioperative Blood Transfusion in Patients Undergoing Gynecologic Surgery: A Systematic Review by Zhongmian Pan, Kittipat Charoenkwan

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Application of Artificial Intelligence Models to Predict the Onset or Recurrence of Neovascular Age-Related Macular Degeneration by Francesco Saverio Sorrentino, Marco Zeppieri, Carola Culiersi, Antonio Florido, Katia De Nadai, Ginevra Giovanna Adamo, Marco Pellegrini, Francesco Nasini, Chiara Vivarelli, Marco Mura, Francesco Parmeggiani

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Correction: Assessing the potential of polygenic scores to strengthen medical risk prediction models of COVID-19

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Combining multi-surface and biotoxicity models to predict cadmium bioavailability and accumulation in a soil collembolan by Simin Li, Jiawen Zhou, Tingting Mu, Tuozheng Wu, Zhu Li, Xin Ke, Longhua Wu, Yongming Luo, Yuanqing Bu

“…MSMs-rBLM model may be a new tool for the prediction of Cd ecological risks and bioaccumulation in soils.…”
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Author Correction: Advanced predictive machine and deep learning models for round-ended CFST column by Feng Shen, Ishan Jha, Haytham F. Isleem, Walaa J.K. Almoghayer, Mohammad Khishe, Mohamed Kamel Elshaarawy

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Risk prediction models for dental caries in children and adolescents: a systematic review and meta-analysis by Peng Zhang, Kang Li, Xijia Wang, Huifei Lu, Dandan Luo, Dunhui Yang, Shuqi Qiu, Haotao Zeng, Xianhai Zeng

“…The search focused on caries prediction models in children and adolescents.Eligibility criteria Eligible studies included observational research (cohort, case–control and cross-sectional designs) that developed risk prediction models for dental caries in children and adolescents aged ≤18 years. …”
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Comparison Airport Traffic Prediction Performance Using BiGRU and CNN-BiGRU Models by Willy Riyadi, Jasmir, Xaverius Sika

“…COVID-19 pandemic has significantly disrupted the aviation industry, highlighting the critical need for accurate airport traffic predictions. This study compares the performance of BiGRU and CNN-BiGRU models to enhance airport traffic forecasting accuracy models from March to December 2020. …”
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Challenges in developing reliable phosphorus predictive models: Unpredictable release under soil redox changes by Filippo Saiano, Riccardo Scalenghe

“…Nevertheless, we were unable to develop a predictive model for soil P desorption based on key intrinsic properties and climate. …”
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Correction: Assessing the potential of polygenic scores to strengthen medical risk prediction models of COVID-19. by Aldo Córdova-Palomera, Csaba Siffel, Chris DeBoever, Emily Wong, Dorothée Diogo, Sandor Szalma

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Accurate prediction of synthesizability and precursors of 3D crystal structures via large language models by Zhilong Song, Shuaihua Lu, Minggang Ju, Qionghua Zhou, Jinlan Wang

“…Leveraging CSLLM, tens of thousands of synthesizable theoretical structures are successfully identified, with their 23 key properties predicted using accurate graph neural network models.…”
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Enhancing Concrete Workability Prediction Through Ensemble Learning Models: Emphasis on Slump and Material Factors by Jiangsong Jiang, Chunhong Xin, Sifei Wu, Wenbing Chen, Hui Li, Zhaolun Ran

“…This study advances concrete workability prediction by integrating ensemble learning models like Random Forest (RF), Extreme Gradient Boosting (XGBoost), adaptive boosting (AdaBoost), and gradient boosted regression trees (GBRTs), and XGBoost showing superior accuracy. …”
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Novel integrative models to predict the severity of inflammation and fibrosis in patients with drug-induced liver injury by Yue Zhang, Chuan Lu, Jingying Xu, Qiqi Ma, Mei Han, Li Ying

“…Then, backward stepwise regression, best subset and logistic regression models were conducted for predicting significant liver inflammation and fibrosis. …”
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EXAMINING THE IMPACT OF FEATURE SELECTION TECHNIQUES ON MACHINE AND DEEP LEARNING MODELS FOR THE PREDICTION OF COVID-19 by Hafiza Zoya Mojahid, Jasni Mohamad Zain, Marina Yusoff, Abdul Basit, Abdul Kadir Jumaat, Mushtaq Ali

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