A comparative approach of machine learning models to predict attrition in a diabetes management program. by Samantha Kanny, Grisha Post, Patricia Carbajales-Dale, William Cummings, Janet Evatt, Windsor Westbrook Sherrill

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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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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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An Informer-based multi-scale model that fuses memory factors and wavelet denoising for tidal prediction by Peng Lu, Yuchen He, Wenhui Li, Yuze Chen, Ru Kong, Teng Wang

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A Near-Real-Time Model for Predicting Electricity Disruptions in Texas During Winter Storms by Jangjae Lee, Sangkeun Lee, Supriya Chinthavali, Stephanie Paal

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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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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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