Toward long-range ENSO prediction with an explainable deep learning model by Qi Chen, Yinghao Cui, Guobin Hong, Karumuri Ashok, Yuchun Pu, Xiaogu Zheng, Xuanze Zhang, Wei Zhong, Peng Zhan, Zhonglei Wang

“…Its evolution is governed by intricate air-sea interactions, posing significant challenges for long-term prediction. In this study, we introduce CTEFNet, a multivariate deep learning model that synergizes convolutional neural networks and transformers to enhance ENSO forecasting. …”
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Artificial Intelligence-Based Prediction Model for Maritime Vessel Type Identification by Hrvoje Karna, Maja Braović, Anita Gudelj, Kristian Buličić

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Physical fitness and frailty index in developing biological age prediction model by Masoud Golpayegany, Saba Amiri, Abbas Haghparast, Maryam Nourshahi

“…This research aimed to develop a comprehensive BA prediction model integrating genetic and epigenetic factors. …”
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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

“…We used three data encoding/imputation strategies and built XGBoost, LightGBM, logistic regression, LSTM, and RNN models to predict next-day extubation. We compared model predictions and actual events to examine how model-driven care might have differed from actual care. …”
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External validation of risk prediction models for post-stroke mortality in Berlin by Jessica L Rohmann, Tobias Kurth, Heinrich J Audebert, Marco Piccininni, Lukas Reitzle

“…Objectives Prediction models for post-stroke mortality can support medical decision-making. …”
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Interformer: an interaction-aware model for protein-ligand docking and affinity prediction by Houtim Lai, Longyue Wang, Ruiyuan Qian, Junhong Huang, Peng Zhou, Geyan Ye, Fandi Wu, Fang Wu, Xiangxiang Zeng, Wei Liu

“…Abstract In recent years, the application of deep learning models to protein-ligand docking and affinity prediction, both vital for structure-based drug design, has garnered increasing interest. …”
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Prediction of permeability of amended soil using ensembled artificial intelligence models by Ankit Kumar, Rohit Ahuja

“…Through comparative analysis, the Gradient Boost with Decision Tree (GB-DTR) model is found to be best-performed model, with R2 = 0.9919. …”
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Research on rock strength prediction model based on machine learning algorithm by Xiang Ding, Mengyun Dong, Wanqing Shen

“…Eight supervised learning algorithms were used to learn the rock compressive strength test data, and eight rock compressive strength prediction models considering multiple factors were established to obtain a better method of predicting rock compressive strength. …”
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Explainable surrogate modeling for predicting temperature separation performance of the vortex tube by Hyo Beom Heo, Jun Ho Lee, Jeong Won Yoon, Sangseok Yu, Byoung Jae Kim, Seokyeon Im, Seung Hwan Park

“…Numerous studies have proposed a data-driven surrogate model to predict the temperature at an outlet. These data-driven models are a narrow model that is suitable for the specific device. …”
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Prediction of Industrial Property Rights Applications using Vector Autoregressive Model by Byeongdeuk Jang, Hyukjoon Kim

Subjects: “…vector autoregressive model…”
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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

“…Methods Here, we examine the ability of models based on Arabidopsis gene expression data to predict tissue identity in other flowering plants. …”
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Predicting models for work outcomes in patients with schizophrenia and its clinical application by Chika Sumiyoshi, Satsuki Ito, Junya Matsumoto, Hidenaga Yamamori, Michiko Fujimoto, Yuka Yasuda, Tomiki Sumiyoshi, Ryota Hashimoto

“…Abstract Negative symptoms and social function have been known to predict work outcomes in patients with schizophrenia. …”
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Artificial neural network model for predicting water inflow into a reservoir by A. N. Shilin, M. A. Bogale, L. A. Konovalova

“…The results obtained show that the models successfully predicted flood runoff over the reservoir.…”
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Construction and evaluation of an aspirin resistance risk prediction model for ischemic stroke by Tianyu Ma, Xue Wang, Yan Song, Junying Liu, Min Zhang

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Bridging Analytical Models and Cfd: Advancing Ammonia Spill Dispersion Predictions by Filippo De Rosa, Pablo Giacopinelli, Felicia Tan, Alexandre Lebas, Christophe Mabilat

“…To address this gap, this study presents a novel modelling approach to predict accurately ammonia behaviour during accidental releases. …”
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Psychometric Evaluation of Large Language Model Embeddings for Personality Trait Prediction by Julina Maharjan, Ruoming Jin, Jianfeng Zhu, Deric Kenne

“…First, we generated text embeddings using 3 LLM architectures (RoBERTa, BERT, and OpenAI) and trained a custom bidirectional long short-term memory model for personality prediction. We compared this approach against zero-shot inference using prompt-based methods. …”
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Review and Evaluation of Slip-ratio-based Void Fraction Prediction Models by HE Wen, HAN Jinyu, ZHAO Chenru, LI Yanlin, BO Hanliang

“…The gas phase content is relatively low, and the velocities of two phases may be unevenly distributed on the cross-section of the channel, resulting in the low accuracy of the slip-ratio-based models. Thus, slip-ratio-based models are not recommended in this range to predict the void fraction. …”

Prediction Model of Asphalt Content of Asphalt Mixture Based on Dielectric Properties by Yanhui Zhong, Yilong Wang, Bei Zhang, Xiaolong Li, Songtao Li, Yanmei Zhong, Meimei Hao, Yanlong Gao

“…Based on the dielectric properties of an asphalt mixture, the prediction model of asphalt content is deduced theoretically using three types of dielectric models: Lichtenecker-Rother (L-R) model, Rayleigh model, and Bottcher equation. …”
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Current Developments in Dementia Risk Prediction Modelling: An Updated Systematic Review. by Eugene Y H Tang, Stephanie L Harrison, Linda Errington, Mark F Gordon, Pieter Jelle Visser, Gerald Novak, Carole Dufouil, Carol Brayne, Louise Robinson, Lenore J Launer, Blossom C M Stephan

“…<h4>Background</h4>Accurate identification of individuals at high risk of dementia influences clinical care, inclusion criteria for clinical trials and development of preventative strategies. Numerous models have been developed for predicting dementia. …”
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Accuracy and precision in DM intake prediction models for lactating dairy cows by N. Mehaba, S. Schrade, L. Eggerschwiler, F. Dohme-Meier, P. Schlegel

“…Finally, the 30-year old Agroscope model emerged as the most accurate and precise in predicting DMI in lactating dairy cows fed a diet consisting of 90–95% of a mixed basal diet (dry and ensiled herbage and corn silage) and of 5–10% concentrates (DM basis).…”
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