Pathway activation model for personalized prediction of drug synergy by Quang Thinh Trac, Yue Huang, Tom Erkers, Päivi Östling, Anna Bohlin, Albin Osterroos, Mattias Vesterlund, Rozbeh Jafari, Ioannis Siavelis, Helena Backvall, Santeri Kiviluoto, Lukas Orre, Mattias Rantalainen, Janne Lehtiö, Soren Lehmann, Olli Kallioniemi, Yudi Pawitan, Trung Nghia Vu

“…Computational models based on the integration of omics data have been used to identify synergistic combinations, but predicting drug synergy remains a challenge. Here, we introduce Drug synergy Interaction Prediction (DIPx), an algorithm for personalized prediction of drug synergy based on biologically motivated tumor- and drug-specific pathway activation scores (PASs). …”
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Prediction of Clinical Bronchiectasis from Asymptomatic Radiological Bronchiectasis by Fan Y, Li Z, Jiang N, Zhou Y, Song J, Yu F, Zhang J, Wang X

“…ROC, a calibration and decision curve were used to assess the predictive performance of our new prediction model.Results: 370 patients (74, 20% with CB) were finally included. …”
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Parameter Optimization of MIMO Fuzzy Optimal Model Predictive Control By APSO by Adel Taieb, Moêz Soltani, Abdelkader Chaari

“…This paper introduces a new development for designing a Multi-Input Multi-Output (MIMO) Fuzzy Optimal Model Predictive Control (FOMPC) using the Adaptive Particle Swarm Optimization (APSO) algorithm. …”
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Two-Layer Predictive Control of a Continuous Biodiesel Transesterification Reactor by Hongyan Shi, Dingding Wang, Decheng Yuan, Tianran Wang

“…A novel two-layer predictive control scheme for a continuous biodiesel transesterification reactor is presented. …”
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Water Supply Network System Control Based on Model Predictive Control by Adel Abdulrahman, Nagib Nasher

“…This paper considers the application of a controller that is approved to be robust to improve the behavior of the water network supply system, to maintain stable operation of the water flow rate, and reduce the operational cost by manipulating the pump speed. The model predictive control (MPC) algorithm is one of the most common automatic control system that has got a wide spread application in process industry. …”
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Data Science Application for Creation of Maternal Morbidity and Mortality Predictive Software by Rúsbel Domínguez-Domínguez, Germán H. Alférez, Verenice González-Mejia, Norbet Donías

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Predictive Beamforming With Active Inference Under Continuous Time-Varying Channels by Naoki Nishio, Tatsuya Otoshi, Masayuki Murata

“…To address this issue, we propose a method that combines hierarchical codebooks with active inference to predict the optimal beam rather than search for it. …”
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Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

“…Given the diverse needs of these pilgrims and the continuous efforts to enhance their experience, we propose an advanced social media classification system based on predictive deep learning. The primary objective of this system is to efficiently classify and analyze social media content related to Hajj and Umrah services. …”
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Design and Practical Evaluation of Robust Model Predictive Wind Turbine Control by Andreas Klein, Thorben Wintermeyer‐Kallen, János Zierath, Kevin Kluge, Dirk Abel, Heike Vallery, Maximilian Basler

“…Due to ever more and ever larger wind turbines (WT), the requirements for WT operation become more complex. Model predictive control (MPC) for WTs shows the potential to handle these requirements and conflicting control objectives in a single optimization‐based controller. …”
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An Integrated Framework for Cryptocurrency Price Forecasting and Anomaly Detection Using Machine Learning by Hani Alnami, Muhammad Mohzary, Basem Assiri, Hussein Zangoti

“…The accurate prediction of cryptocurrency prices is crucial due to the volatility and complexity of digital asset markets, which pose significant challenges to traders, investors, and researchers. …”
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Development and external validation of a nomogram prediction model based on quantitative coronary angiography for predicting ischemic lesions: a multi-centre study by Shuai Yang, Shuai Yang, Shuang Leng, Shuang Leng, Zhouchi Wang, Jiang Ming Fam, Jiang Ming Fam, Adrian Fatt Hoe Low, Adrian Fatt Hoe Low, Ru-San Tan, Ru-San Tan, Ping Chai, Ping Chai, Lynette Teo, Lynette Teo, Chee Yang Chin, Chee Yang Chin, John C. Allen, Mark Yan-Yee Chan, Mark Yan-Yee Chan, Khung Keong Yeo, Khung Keong Yeo, Aaron Sung Lung Wong, Aaron Sung Lung Wong, Soo Teik Lim, Soo Teik Lim, Qinghua Wu, Liang Zhong, Liang Zhong, Liang Zhong

“…For per-patient analysis, the corresponding values were 85.8%, 85.7%, 86.0% in the development cohort and 82.2%, 83.3%, 81.1% in the validation cohort.ConclusionThe nomogram may be useful for predicting ischemic lesions using QCA measurements and the LASSO regression algorithm, with external validation indicating potential predictive value in cardiology care settings.…”
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Surfactants Adsorption onto Algerian Rock Reservoir for Enhanced Oil Recovery Applications: Prediction and Optimization Using Design of Experiments, Artificial Neural Networks, and Genetic Algorithm (GA) by Kahina Imene Benramdane, Mohamed El Moundhir Hadji, Mohamed Khodja, Nadjib Drouiche, Bruno Grassl, Seif El Islam Lebouachera

“…Compared to DOE-based models, ANN exhibited superior predictive accuracy, with a performance factor (PF/3) of 0.00157 and the same MSE. …”
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A Novel Grey Prediction Model: A Hybrid Approach Based on Extension of the Fractional Order Discrete Grey Power Model with the Polynomial-Driven and PSO-GWO Algorithm by Baohua Yang, Xiangyu Zeng, Jinshuai Zhao

“…Background: This study addresses the challenge of predicting data sequences characterized by a mix of partial linearity and partial nonlinearity. …”
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Annotation-free deep learning algorithm trained on hematoxylin & eosin images predicts epithelial-to-mesenchymal transition phenotype and endocrine response in estrogen receptor-positive breast cancer by Kaimin Hu, Yinan Wu, Yajing Huang, Meiqi Zhou, Yanyan Wang, Xingru Huang

“…Our classifier achieved a predicting accuracy of 81.25%, and 88.7% slides labeled as endocrine resistant were predicted as the mesenchymal-phenotype, while 75.6% slides labeled as sensitive were predicted as the epithelial-phenotype. …”
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Research on Leak Detection and Localization Algorithm for Oil and Gas Pipelines Using Wavelet Denoising Integrated with Long Short-Term Memory (LSTM)–Transformer Models by Yunbin Ma, Zuyue Shang, Jie Zheng, Yichen Zhang, Guangyuan Weng, Shu Zhao, Cheng Bi

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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

“…Optimization using GTO resulted in a 6.71% improvement in kerf deviation prediction accuracy compared to experimental values, while ZOA achieved a 2.37% improvement. …”
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Predictive modeling and optimization of noise emissions in a palm oil methyl ester-fueled diesel engine using response surface methodology and artificial neural network integrated with genetic algorithm by J.M. Zikri, M.S.M. Sani, M.F.F.A. Rashid, J. Muriban, G.S. Prayogo

“…This research examines the predictive performance of two modeling techniques—Response Surface Methodology (RSM) and an Artificial Neural Network enhanced by a Genetic Algorithm (ANN-GA)—in relation to noise emission levels from a single-cylinder diesel engine running on palm oil methyl ester (POME). …”
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Interpretable Reinforcement Learning for Sequential Strategy Prediction in Language-Based Games by Jun Zhao, Jintian Ji, Robail Yasrab, Shuxin Wang, Liang Yu, Lingzhen Zhao

“…However, existing models often struggle with poor adaptability and limited interpretability when applied to dynamic language prediction tasks such as <b>Wordle</b>. To address these challenges, this study proposes an interpretable reinforcement learning framework based on an Enhanced Deep Deterministic Policy Gradient (Enhanced-DDPG) algorithm. …”
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Criminal Algorithms and Their Punishment in Modern Constitutionalism by Carlo Piparo, Radovan Blažek

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