Harnessing synergy of machine learning and nature-inspired optimization for enhanced compressive strength prediction in concrete by Abba Bashir, Esar Ahmad, Shashivendra Dulawat, Sani I. Abba

“…Concrete made with additives like slag and fly ash has revolutionized construction by reducing carbon emissions, minimizing waste, lowering labor costs, and enhancing durability and accuracy. Predicting the compressive strength (CS) is vital for achieving optimal performance. …”
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Machine learning for classifying chronic kidney disease and predicting creatinine levels using at-home measurements by Brady Metherall, Anna K. Berryman, Georgia S. Brennan

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Predicting nighttime black ice using atmospheric data for efficient winter road maintenance patrols by Jinhwan Jang

“…The novelty of this study lies in predicting road icing using only readily available atmospheric data, which eliminates the need for costly road weather sensors. …”
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HPGCN: A graph convolutional network-based prediction model for herbal heat/cold properties by Qikai Niu, Jing’ai Wang, Hongtao Li, Lin Tong, Haiyu Xu, Weina Zhang, Ziling Zeng, Sihong Liu, Wenjing Zong, Siqi Zhang, Siwei Tian, Huamin Zhang, Bing Li

Subjects: “…Herbal property prediction…”
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A machine learning-based model for predicting paroxysmal and persistent atrial fibrillation based on EHR by Yuqi Zhang, Sijin Li, Peibiao Mai, Yanqi Yang, Niansang Luo, Chao Tong, Kuan Zeng, Kun Zhang

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InceptionDTA: Predicting drug-target binding affinity with biological context features and inception networks by Mahmood Kalemati, Mojtaba Zamani Emani, Somayyeh Koohi

Subjects: “…Drug-target binding affinity prediction…”
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Prediction of digestible energy requirement in growing finishing stage of pigs using machine learning models by Nibas Chandra Deb, Jayanta Kumar Basak, Sijan Karki, Elanchezhian Arulmozhi, Dae Yeong Kang, Niraj Tamrakar, Eun Wan Seo, Junghoo Kook, Myeong Yong Kang, Hyeon Tae Kim

“…Most importantly, the sensitivity analysis revealed that BW exerted the most significant impact on predicting DER among other variables. In conclusion, the study suggested that RFR model can precisely predict DER, offering valuable insights for pig farmers to enhance their understanding of DE management.…”
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Development of an Efficient and Generalized MTSCAM Model to Predict Liquid Chromatography Retention Times of Organic Compounds by Mengdie Fan, Chenhui Sang, Hua Li, Yue Wei, Bin Zhang, Yang Xing, Jing Zhang, Jie Yin, Wei An, Bing Shao

“…Accurate prediction of liquid chromatographic retention times is becoming increasingly important in nontargeted screening applications. …”
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Predictive factors for extubation success in very low and extremely low birth weight preterm infants by Nilson Willamy Bastos de Souza Júnior, Tathiane Ribeiro Rosa, Jane Cecília Kreling Cerântola, Ligia Silvana Lopes Ferrari, Vanessa Suziane Probst, Josiane Marques Felcar

“…GA and post-extubation arterial partial pressure of carbon dioxide (PaCO~2~) were predictive of extubation success. Infants from FG had lower GA and BW, while those from SG had higher weight at extubation and lower post-extubation PaCO~2~…”
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COVID-19 death toll predictions show that triggering counterfactual thinking deteriorates judgmental performance by Matthias Seifert, Jeeva Somasundaram

“…Results Here we show that individuals who engaged in thinking about “interventions that could have led to an alternative evolution of the death toll” prior to making forecasts exhibit greater judgmental bias in their predictions compared to the control group. Specifically, subjects in the treatment group tend to generate upward counterfactuals and underestimate the death toll, potentially due to anchoring on more favorable scenarios and insensitivity to trend changes. …”
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Comparative Analysis of Federated and Centralized Learning Systems in Predicting Cellular Downlink Throughput Using CNN by Kukuh Nugroho, Hendrawan, Iskandar

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Predictive modeling and optimization of SI engine performance and emissions with GEM blends using ANN and RSM by Farooq Shaik, D. Vinay Kumar, N. Channa Keshava Naik, G. Radha Krishna, T. M. Yunus Khan, Abdul Saddique Shaik, Abdulrajak Buradi, Addisu Frinjo Emma

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Dual graph-embedded fusion network for predicting potential microbe-disease associations with sequence learning by Junlong Wu, Liqi Xiao, Liu Fan, Lei Wang, Xianyou Zhu, Xianyou Zhu

“…By combining advanced graph-based and sequence-based learning techniques, DuGEL addresses the limitations of existing methods and provides a robust framework for the prediction of microbe-disease associations. To evaluate the performance of DuGEL, we conducted comprehensive comparative experiments and case studies based on two databases, HMDAD, and Disbiome to demonstrate that DuGEL can effectively predict potential microbe-disease associations.…”
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Predicting roadkill: a regional-scale model for the Northern Tamandua integrating environmental and road characteristics by Silvio Boyat, Esmeralda Arévalo-Huezo

“…The final model had an excellent predictive performance (AUC = 0.989) and identified 108.7 km of road sections throughout the region as high risk, mainly found on primary roads. …”
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Predicting turbidity dynamics in small reservoirs in central Kenya using remote sensing and machine learning by Stefanie Steinbach, Anna Bartels, Andreas Rienow, Bartholomew Thiong’o Kuria, Sander Jaap Zwart, Andrew Nelson

“…Our results suggest that short- and longer-term turbidity prediction can inform reservoir siting and management. …”
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LSTM-Based Time Series Prediction Model: A Case Study with YFinance Stock Data by Yu Yimiao

“…However, the model exhibits poor performance in predicting high-frequency fluctuations, with an R2 of only -0.1, indicating a weak ability to capture high-frequency volatility.…”
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Advancing the accuracy of tyrosinase inhibitory peptides prediction via a multiview feature fusion strategy by Watshara Shoombuatong, Nalini Schaduangrat, Nutta Homdee, Saeed Ahmed, Pramote Chumnanpuen

“…To date, a few machine learning-based models have been proposed for predicting TIPs, but their predictive performance remains unsatisfactory. …”
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DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

“…Therefore, considering the general findings, the study identified five Data Mining algorithms as appropriate and most commonly used for prediction of student teachers’ performance in ICT. …”
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A comparative study of turbulence models for predicting the aerodynamic drag of a spin-stabilized projectile by Quang Tuan Nguyen

“…Introduction/purpose: In this research, the influence of different turbulence models on the aerodynamic drag prediction of a generic spin-stabilized projectile was analyzed. …”
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A A three-phase induction motor dynamic framework regulated by predictive and intelligent optimizations. by Shaswat Chirantan, Bibhuti Bhusan Pati

“… The role of Model Predictive Control (MPC) as a fundamental optimization tool in modern control systems is increasingly emphasized. …”
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