Development and validation of a decision tree model for prediction of insomnia risk among ischemic stroke convalescence patients by Xuefeng Sun, Zilin Wang, Yuqing Song, Deyu Cong, Shu Sun, Xinye Zhang, Ye Zhang, Hongshi Zhang

“…While the interaction of clinical, psychological, and social factors remains unclear, developing a predictive model system is urgently needed. Currently, few studies have established insomnia risk prediction models. …”
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A deep learning model to predict Ki-67 positivity in oral squamous cell carcinoma by Francesco Martino, Gennaro Ilardi, Silvia Varricchio, Daniela Russo, Rosa Maria Di Crescenzo, Stefania Staibano, Francesco Merolla

“…Aside from classification, detection, and segmentation models, predictive models are gaining traction since they can impact diagnostic processes and laboratory activity, lowering consumable usage and turnaround time. …”
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Robust Path Tracking Control with Lateral Dynamics Optimization: A Focus on Sideslip Reduction and Yaw Rate Stability Using Linear Quadratic Regulator and Genetic Algorithms by Karrar Y. A. Al-bayati, Ali Mahmood, Róbert Szabolcsi

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Enhancing cybersecurity via attribute reduction with deep learning model for false data injection attack recognition by Faheed A.F. Alrslani, Manal Abdullah Alohali, Mohammed Aljebreen, Hamed Alqahtani, Asma Alshuhail, Menwa Alshammeri, Wafa Sulaiman Almukadi

“…The ARDL-FDIAR technique uses Z-score normalization to scale the input data. The attribute reduction process gets invoked using the modified Lemrus optimization algorithm (MLOA) to choose optimal feature sets. …”
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A Distribution Network Expansion Project Classification Model Based on Data Augmentation and Dimensionality Reduction Method by Xin ZHOU, Jingxing LIN, Zhiwei XIE, Zheng ZHANG, Ruduo LIANG, Zuhong OU

“…Based on the data of a distribution network expansion project of a power supply bureau, the simulation results show that the classification accuracy of the algorithm used in this paper is better than other algorithms. …”
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A novel approach for the effective prediction of cardiovascular disease using applied artificial intelligence techniques by Azka Mir, Attique Ur Rehman, Tahir Muhammad Ali, Sabeen Javaid, Maram Fahaad Almufareh, Mamoona Humayun, Momina Shaheen

“…Methods In this paper, we have utilized machine learning algorithms to predict cardiovascular disease on the basis of symptoms such as chest pain, age and blood pressure. …”
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A similarity-based multi-objective test optimization technique using search algorithm by Amir Sohail Habib, Saif Ur Rehman Khan, Shahid Hussain, Naseem Ibrahim, Habib un Nisa, Abdullah Yousafzai

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Construction of a sleep staging prediction model for obstructive sleep apnea patients based on hypoxia parameters by YANG Mengdie，PENG Cheng，CUI Yiran，XU Shaorong，WANG Yan

“…The ANN model was constructed using a feed-forward structure incorporating a multilayer perceptron（MLP）with a back-propagation algorithm. Predictive performance was assessed using receiver operating characteristic（ROC）curves.Results Compared with the hypoxia parameters in NREM stage，e-minSpO2 and r.DSpO2 were lower，and ΔSpO2，d.DSpO2，ODR，ORR，T90，d.T90，r.T90，and ST90，d.ST90，r.ST90 were higher in REM stage（P<0.05）. …”
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Pan-cancer predictive survival model development and evaluation using electronic health record and genetic data across 10 cancer types by Jurgita Gammall, Alvina G. Lai

“…We compare the performance of different machine learning algorithms and assess the added value of genetic information in cancer prognosis. …”
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MOUD 2.0: a clinical algorithm and implementation evaluation protocol for sublingual and injectable buprenorphine treatment of opioid use disorder by Brandon L. Joa, Eric N. Fung, Michael S. Weinstein, Lara C. Weinstein, Lara C. Weinstein

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How Predictable Is Electric Vehicle Adoption? Exploring the Broader Role of Renewables in Transportation Using a Data-Driven Approach by Simona-Vasilica Oprea, Adela Bara

“…Equally important is the capacity to predict the likelihood of EV adoption. A classification model is proposed, embedding several cutting-edge classifiers. …”
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Development and validation of a machine learning-based survival prediction model for Asian glioblastoma patients using the SEER database and Chinese data by Denglin Li, Luxin Zhang, Lifei Xu, Renhe Zhai, Hanyu Gao, Junlan Gao, Minghai Wei, Ningwei Che, Yeting He

“…Our study attempted to investigate the independent predictors of overall survival (OS) and cancer-specific survival (CSS) in Asian patients with glioblastoma and establish predictive models for the OS and CSS of Asian patients with glioblastoma based on the machine learning algorithms. …”
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PSO-NMPC control strategy based path tracking control of mining LHD (scraper) by Ya Liu, Ping-an Peng, Li-guan Wang, Jia-xi Wu, Ming-yu Lei, Chao-wei Zhang, Ru Lei

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Artificial Intellect Systems in Today’s Economic Environment by N. V. Barinova, V. R. Barinov

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Crude Oil and Hot-Rolled Coil Futures Price Prediction Based on Multi-Dimensional Fusion Feature Enhancement by Yongli Tang, Zhenlun Gao, Ya Li, Zhongqi Cai, Jinxia Yu, Panke Qin

“…In addition, the significance and stability of the model performance were verified by statistical methods such as a paired t-test and ANOVA analysis of variance. This MDFFE algorithm offers a robust and practical approach for predicting commodity futures prices. …”
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A Semi-Supervised-Learning-Aided Explainable Belief Rule-Based Approach to Predict the Energy Consumption of Buildings by Sami Kabir, Mohammad Shahadat Hossain, Karl Andersson

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Preliminary Evaluation of an Advanced Ventilation-Control Algorithm to Optimise Microclimate in a Commercial Broiler House by Kehinde Favour Daniel, Lak-yeong Choi, Se-yeon Lee, Chae-rin Lee, Ji-yeon Park, Jinseon Park, Se-woon Hong

“…This study aims to improve the microclimate conditions in a mechanically ventilated broiler house by proposing and evaluating a ventilation-control algorithm based on heat-energy balance analysis. The new algorithm is designed to optimise the ventilation-rate requirement and thereby improve control of the indoor temperature. …”
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Stunting Prediction Modeling in Toddlers Using a Machine Learning Approach and Model Implementation for Mobile Application by Eko Abdul Goffar, Rosa Eliviani, Lili Ayu Wulandhari

“…The literature review section discusses the factors that influence stunting, and these factors are used as features to build a stunting prediction model. Then the features were used to build a model with three machine learning algorithms Extreme Gradient Boosting (XGBoost), Random Forest, and K-Nearest Neighbor (KNN) to build and evaluate models that predict stunting. …”
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A novel metaheuristic approach for simultaneous loss minimization and torque ripple reduction of DTC- IM driven EV by Anjan Kumar Sahoo

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Intra-articular Glenoid Fracture Managed by Arthroscopic Fixation and Open Reduction and Internal Fixation Techniques: An Analytical Study by Prahalad K Singhi, Sivakumar Raju, Chidambaram Muthu, Gopi Kumarasamy, Vinoth Thangamani, Muthukishore Marichamy

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