New insight into viscosity prediction of imidazolium-based ionic liquids and their mixtures with machine learning models by Amir Hossein Sheikhshoaei, Ali Sanati

“…Machine learning (ML) models have been implemented, and their performance in viscosity prediction for IL mixtures was compared with a molecular-based model, ePC-SAFT-FVT (ePC-FVT-MB), and an ion-based model, ePC-SAFT-FVT (ePC-FVT-MB). …”
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Improving drug-drug interaction prediction via in-context learning and judging with large language models by He Qi, He Qi, Xiaoqiang Li, Chengcheng Zhang, Tianyi Zhao, Tianyi Zhao

“…To further refine predictions, we employ GPT-4 as a discriminator to assess the relevance of predictions generated by multiple LLMs.ResultsDDI-JUDGE achieves the best performance among all models in both zero-shot and few-shot settings, with an AUC of 0.642/0.788 and AUPR of 0.629/0.801, respectively. …”
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Predicting individual traits from models of brain dynamics accurately and reliably using the Fisher kernel by Christine Ahrends, Mark W Woolrich, Diego Vidaurre

“…One reason why these dynamic patterns are not usually considered is that they have to be described by complex, high-dimensional models; and it is unclear how best to use these models for prediction. …”
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Impact of a multiple oversampling technique-based assessment framework on shallow rockburst prediction models by Guozhu Rao, Guozhu Rao, Yunzhang Rao, Yunzhang Rao, Yangjun Xie, Qiang Huang, Jiazheng Wan, Jiyong Zhang

“…The occurrence of class-imbalanced datasets is a frequent observation in natural science research, emphasizing the paramount importance of effectively harnessing them to construct highly accurate models for rockburst prediction. Initially, genuine rockburst incidents within a burial depth of 500 m were sourced from literature, revealing a small dataset imbalance issue. …”
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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…These findings indicate the effectiveness of LPBSA in enhancing predictive modeling for critical health conditions.…”
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Adaptability of prognostic prediction models for patients with acute coronary syndrome during the COVID-19 pandemic by Takeshi Nakamura, Satoaki Matoba, Masahiro Nishi, Kenji Yanishi

“…Background The detrimental repercussions of the COVID-19 pandemic on the quality of care and clinical outcomes for patients with acute coronary syndrome (ACS) necessitate a rigorous re-evaluation of prognostic prediction models in the context of the pandemic environment. …”
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Hyperspectral Prediction Models of Chlorophyll Content in <i>Paulownia</i> Leaves under Drought Stress by Yamei Zhang, Guangxin Ru, Zhenli Zhao, Decai Wang

“…Based on the prediction accuracy and the uniformity of different leaf positions, the optimal model was systematically explored. …”
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Chemical Composition-Driven Machine Learning Models for Predicting Ionic Conductivity in Lithium-Containing Oxides by Yudai IWAMIZU, Kota SUZUKI, Michiyo KAMIYA, Naoki MATSUI, Kuniharu NOMOTO, Satoshi HORI, Masaaki HIRAYAMA, Ryoji KANNO

“…Thus, new models demonstrating improved prediction ability must be developed. …”
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Deflection Predictions of Tapered Cellular Steel Beams Using Analytical Models and an Artificial Neural Network by Amine Osmani, Rabee Shamass, Konstantinos Daniel Tsavdaridis, Felipe Piana Vendramell Ferreira, Abdelwahhab Khatir

“…The deflections predicted by the analytical and ANN models were compared with finite element results, showing good agreement.…”
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Air quality prediction based on factor analysis combined with Transformer and CNN-BILSTM-ATTENTION models by Shuyuan Liu, Yang Hu

“…Abstract This study presents an innovative air quality prediction framework that integrates factor analysis with deep learning models for precise prediction of original variables. …”
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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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Predicting Olympic Medal Performance for 2028: Machine Learning Models and the Impact of Host and Coaching Effects by Zhenkai Zhang, Tengfei Ma, Yunpeng Yao, Ningjia Xu, Yujie Gao, Wanwan Xia

“…This study develops two machine learning models to predict the medal performance of countries at the 2028 Olympic Games while systematically analyzing and quantifying the impacts of the host effect and exceptional coaching on medal gains. …”
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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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