A Multimodal Deep Learning Model Integrating CNN and Transformer for Predicting Chemotherapy-Induced Cardiotoxicity by Ahmed Bouatmane, Abdelaziz Daaif, Abdelmajid Bousselham, Bouchra Bouihi, Omar Bouattane

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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

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Enhanced Hybrid Deep Learning Model With Improved Self-Attention Mechanism for Legal Judgment Prediction by G. Sukanya, J. Priyadarshini

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Optimized Prediction of Weapon Effectiveness in BVR Air Combat Scenarios Using Enhanced Regression Models by Andre R. Kuroswiski, Annie S. Wu, Angelo Passaro

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Enhancing Engineering and STEM Education With Vision and Multimodal Large Language Models to Predict Student Attention by Luis Marquez-Carpintero, Diego Viejo, Miguel Cazorla

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An Explainable Model Using Graph-Wavelet for Predicting Biophysical Properties of Proteins and Measuring Mutational Effects by Shreya Mishra, Neetesh Pandey, Atul Rawat, Divyanshu Srivastava, Arjun Ray, Vibhor Kumar

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Construction of a predictive model for concurrent infection in liver failure patients based on prognostic nutritional index and inflammatory cytokine analysis by Hong Yang, Bin Zhang, Chun Yu, Xiao Zhu

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Development of a Success Prediction Model for Crowdfunding Based on Machine Learning Reflecting ESG Information by Jiyoung Park, Hyung Jong Na, Hyungjoon Kim

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Prediction of State-of-Health and Remaining-Useful-Life of Battery Based on Hybrid Neural Network Model by Le Thi Minh Lien, Vu Quoc Anh, Nguyen Duc Tuyen, Goro Fujita

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Enhancing Time-Series Prediction with Temporal Context Modeling: A Bayesian and Deep Learning Synergy by Habib Irani, Vangelis Metsis

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A Mathematical Model for Prediction the Embedment Depth of the Contiguous Piles Used in the Interchange of Zakho Entrance by Najdat S. Akrawi, Shimal A. Ahmed

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Establishing a preoperative predictive model for gallbladder adenoma and cholesterol polyps based on machine learning: a multicentre retrospective study by Yubing Wang, Chao Qu, Jiange Zeng, Yumin Jiang, Ruitao Sun, Changlei Li, Jian Li, Chengzhi Xing, Bin Tan, Kui Liu, Qing Liu, Dianpeng Zhao, Jingyu Cao, Weiyu Hu

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Prediction of Ground Subsidence Risk in Urban Centers Using Underground Characteristics Information by Sungyeol Lee, Jaemo Kang, Jinyoung Kim

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

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Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle by Rachappa Jopate, Piyush Kumar Pareek, DivyaJyothi M. G, Ariam Saleh Zuwayid Juma Al Hasani

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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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Establishing a long-term predictive model for aggressive behavior in schizophrenia: a 21-year longitudinal study in rural China by Hui Jin, Hui Jin, Cong Wang, Cong Wang, Yi-Yue Yang, Yi-Yue Yang, Lie Zhou, Lie Zhou, Yun Xiao, Yun Xiao, Yang Wen, Yang Wen, Jawad Ahmad, Jawad Ahmad, Yun-Fei Mu, Yun-Fei Mu, Jia Cai, Ming Li, Wei Luo, Xiao-Fei Zhou, Jian-Jun Luo, Bo Liu, Eric Yu-Hai Chen, Mao-Sheng Ran, Mao-Sheng Ran

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A Larval “Recruitment Kernel” to Predict Hatching Locations and Quantify Recruitment Patterns by Wei Shi, Leon Boegman, Shiliang Shan, Yingming Zhao, Josef D. Ackerman, Zachary Amidon, Aidin Jabbari, Edward Roseman

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Toward a Multi‐Representational Approach to Prediction and Understanding, in Support of Discovery in Hydrology by Luis A. De la Fuente, Hoshin V. Gupta, Laura E. Condon

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Perspective: How complex in vitro models are addressing the challenges of predicting drug-induced liver injury by K. Taylor, R. Ram, R. Ram, L. Ewart, C. Goldring, G. Russomanno, G. P. Aithal, T. Kostrzewski, C. Bauch, J. M. Wilkinson, J. M. Wilkinson, S. Modi, J. G. Kenna, J. G. Kenna, J. Bailey, J. Bailey

“…Predicting which drugs might have the potential to cause drug-induced liver injury (DILI) is highly complex and the current methods, 2D cell-based models and animal tests, are not sensitive enough to prevent some costly failures in clinical trials or to avoid all patient safety concerns for DILI post-market. …”
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