Exploration-based learning of a stabilizing controller predicts locomotor adaptation by Nidhi Seethapathi, Barrett C. Clark, Manoj Srinivasan

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Machine learning approaches for predicting energy and exergy efficiency in solar still by Somayeh Davoodabadi Farahani, Mohammad Javad Zarei, Hakan F. Oztop

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Artificial Neural Network Individualised Prediction of Time to Colorectal Cancer Surgery by N. J. Curtis, G. Dennison, E. Salib, D. A. Hashimoto, N. K. Francis

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Improving Cardiovascular Disease Prediction With Deep Learning and Correlation-Aware SMOTE by Maria Trigka, Elias Dritsas

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Risk Prediction Score for Thermal Mapping of Pharmaceutical Transport Routes in Brazil by Clayton Gerber Mangini, Nilsa Duarte da Silva Lima, Irenilza de Alencar Nääs

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Multibranch Adaptive Fusion Graph Convolutional Network for Traffic Flow Prediction by Xin Zan, Jasmine Siu Lee Lam

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Climate change impacts on the predicted geographic distribution of Betula tianschanica Rupr by Hang Zhou, Hang Zhou, Ao Li, Ao Li, Xuequn Luo, Xuequn Luo, Jiafeng Wang, Jiafeng Wang, Yihong Xie, Zhongping Lin, Donglai Hua

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Enhanced slope stability prediction using ensemble machine learning techniques by Devendra Kumar Yadav, Swarup Chattopadhyay, Debi Prasad Tripathy, Pragyan Mishra, Pritiranjan Singh

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Research on Efficient Prediction and Suppression of Electromagnetic Interference in Electric Drive Systems by Ruoxi Tan, Shangbin Ye, Qianlei Peng, Changhong Du, Zeyan Zhou

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Customer Churn Prediction Approach Based on LLM Embeddings and Logistic Regression by Meryem Chajia, El Habib Nfaoui

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Integrated analyses and a novel nomogram for the prediction of significant fibrosis in patients by Mengxin Lu, Shuai Tao, Xinyan Li, Qunling Yang, Cong Du, Weijia Lin, Shuangshuang Sun, Conglin Zhao, Neng Wang, Qiankun Hu, Yuxian Huang, Qiang Li, Yi Zhang, Liang Chen

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An adaptive dual distillation framework for efficient remaining useful life prediction by Xiang Cheng, Jun Kit Chaw, Shafrida Sahrani, Mei Choo Ang, Saraswathy Shamini Gunasekaran, Moamin A. Mahmoud, Halimah Badioze Zaman, Yanfeng Zhao, Fuchen Ren

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Prediction of Human Papillomavirus-Host Oncoprotein Interactions Using Deep Learning by Sheila Santa, Samuel Kojo Kwofie, Kwasi Agyenkwa-Mawuli, Osbourne Quaye, Charles A Brown, Emmanuel A Tagoe

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An engineering method of aerodynamic heating prediction for hypersonic blunt body vehicles by Jimin Chen, Guoyi He

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A general approach for predicting the behavior of the Supreme Court of the United States. by Daniel Martin Katz, Michael J Bommarito, Josh Blackman

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On the estimation of inverse-probability-of-censoring weights for the evaluation of survival prediction error. by Thomas Prince, Andrea Bommert, Jörg Rahnenführer, Matthias Schmid

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Scanning Micromirror Calibration Method Based on PSO-LSSVM Algorithm Prediction by Yan Liu, Xiang Cheng, Tingting Zhang, Yu Xu, Weijia Cai, Fengtian Han

“…The objective is to establish a correspondence between the actual deflection angle of the micromirror and the output of the measurement system employing a regression algorithm, thereby enabling the prediction of the tilt angle of the micromirror. The decision factor (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msup><mi>R</mi><mn>2</mn></msup></mrow></semantics></math></inline-formula>) for this model at the <i>x</i>-axis reaches a value of 0.9947.…”
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Application of machine learning in depression risk prediction for connective tissue diseases by Leilei Yang, Yuzhan Jin, Wei Lu, Xiaoqin Wang, Yuqing Yan, Yulan Tong, Dinglei Su, Kaizong Huang, Jianjun Zou

“…Abstract This study retrospectively collected clinical data from 480 patients with connective tissue diseases (CTDs) at Nanjing First Hospital between August 2019 and December 2023 to develop and validate a multi-classification machine learning (ML) model for assessing depression risk. Addressing the limitations of traditional assessment tools, six ML models were constructed using univariate analysis and the LASSO algorithm, with the categorical boosting (Catboost) model emerging as the best performer, demonstrating strong predictive ability across different depression severity levels (none_F1 = 0.879, mild_F1 = 0.627, moderate and severe_F1 = 0.588). …”
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Halal or Not: Knowledge Graph Completion for Predicting Cultural Appropriateness of Daily Products by Van Thuy Hoang, Tien-Bach-Thanh do, Jinho Seo, Seung Charlie Kim, Luong Vuong Nguyen, Duong Nguyen Minh Huy, Hyeon-Ju Jeon, O-Joun Lee

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DKA Prediction in Children Using Artificial Intelligence: Improved Emergency Care by Arifa Parveen, Mohsina Riffat, Sarang Shaikh

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