Improving Surgical Site Infection Prediction Using Machine Learning: Addressing Challenges of Highly Imbalanced Data by Salha Al-Ahmari, Farrukh Nadeem

“…Machine learning (ML) has demonstrated potential in predicting SSIs; however, the challenge of addressing imbalanced class ratios remains. …”
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Enhancing Heart Attack Prediction: Feature Identification from Multiparametric Cardiac Data Using Explainable AI by Muhammad Waqar, Muhammad Bilal Shahnawaz, Sajid Saleem, Hassan Dawood, Usman Muhammad, Hussain Dawood

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The algorithm for selection of interval of parameters recalculation of control and management objects in automatic control systems of process engineering by A. H. Тыныныка

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A Hybrid Three-Staged, Short-Term Wind-Power Prediction Method Based on SDAE-SVR Deep Learning and BA Optimization by Ruiqin Duan, Xiaosheng Peng, Cong Li, Zimin Yang, Yan Jiang, Xiufeng Li, Shuangquan Liu

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The Effect of Resampling Techniques on Model Performance Classification of Maternal Health Risks by Nia Mauliza, Aisha Shakila Iedwan, Yoga Pristyanto, Anggit Dwi Hartanto, Arif Nur Rohman

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Parameter estimation in solar power plant systems: a comparative study of recursive and iterative techniques by Kiavash Hossein Sadeghi, Mahmood Shafikhah, Arash Marashian, Emad Roshandel, Abolhassan Razminia

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Exploring the Role of Artificial Intelligence in Wastewater Treatment: A Dynamic Analysis of Emerging Research Trends by Javier De la Hoz-M, Edwan Anderson Ariza-Echeverri, Diego Vergara

Subjects: “…effluent prediction…”
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Current Applications, Challenges, and Future Directions of Artificial Intelligence in Emergency Medicine: A Narrative Review by Mehrdad Farrokhi, Amir H Fallahian, Erfan Rahmani, Ali Aghajan, Morteza Alipour, Parisa Jafari Khouzani, Hossein Boustani Hezarani, Hamed Sabzehie, Mohammad Pirouzan, Zahra Pirouzan, Behnaz Dalvandi, Reza Dalvandi, Parisa Doroudgar, Habib Azimi, Fatemeh Moradi, Amitis Nozari, Maryam Sharifi, Hamed Ghorbani, Sara Moghimi, Fatemeh Azarkish, Soheil Bolandi, Hooman Esfahani, Sara Hosseinmirzaei, Arezou Niknam, Farzaneh Nikfarjam, Parham Talebi Boroujeni, Mahyar Noorbakhsh, Parham Rahmani, Fatemeh Rostamian Motlagh, Khadijeh Harati, Masoud Farrokhi, Sina Talebi, Lida Zare Lahijan

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Machine learning ensemble technique for exploring soil type evolution by Xiangyuan Wu, Kening Wu, Shiheng Hao, Er Yu, Jinghui Zhao, Yan Li

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Attitude-Predictive Control of Large-Diameter Shield Tunneling: PCA-SVR Machine Learning Algorithm Application in a Case Study of the Zhuhai Xingye Express Tunnel by Hui Li, Yijun Tan, Decheng Zeng, Dong Su, Shiye Qiao

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Real-Time Optimization Improved Model Predictive Control Trajectory Tracking for a Surface and Underwater Joint Observation System Based on Genetic Algorithm–Fuzzy Control by Qichao Wu, Yunli Nie, Shengli Wang, Shihao Zhang, Tianze Wang, Yizhe Huang

“…Aiming at the high-precision trajectory tracking problem of the new surface and underwater joint observation system (SUJOS) in the ocean remote sensing monitoring mission under complex sea conditions, especially at the problem of excessive tracking errors and slow convergence of actual trajectory oscillations caused by the wide range of angular changes in the motion trajectory, a real-time optimization improved model predictive control (IMPC) trajectory tracking method based on fuzzy control is proposed. …”
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Voltage and frequency regulation in wind penetrated deregulated power system using an electric vehicle and IPFC assisted model predictive controller by Vineet Kumar, Vineet Kumar, Ark Dev

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Prediction of new candidate proteins and analysis of sub-modules and protein hubs associated with seed development in rice (Oryza sativa) using an ensemble network-based systems bi... by M. R. P. De Silva, J. W. J. K. Weeraman, S. Piyatissa, P. C. Fernando

“…Using a list of known seed development proteins from the Gene Ontology (GO) knowledgebase and literature, novel candidate proteins for seed development were predicted using an ensemble of network-based algorithms, including Majority Voting, Hishigaki Algorithm, Functional Flow, and Random Walk with Restart, which were selected based on their popularity and usability. …”
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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

Subjects: “…IWOA whale optimization algorithm…”
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Method on PAPR reduction in digital beam-forming by Lu LIU, Guoqing ZHAO

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Predicting Rolling Element Bearings’ Deterioration Vibration Trend based on Limited Historical Data for a Desired Confidence Level using Machine Learning Algorithms by Mohammad Reza Seif, Somaye Mohammadi, Parham Rahimi, Mehdi Behzad

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Advancing flood susceptibility prediction: A comparative assessment and scalability analysis of machine learning algorithms via artificial intelligence in high‐risk regions of Pakistan by Mirza Waleed, Muhammad Sajjad

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Prediction of 5-year postoperative survival and analysis of key prognostic factors in stage III colorectal cancer patients using novel machine learning algorithms by Wei Zhang, Yan Li, Jinghan Jia, Yuhang Yang, Yuyuan Hu, Yanhong Wang, Jinxi Wang

“…ObjectiveThis study explores the predictive value of clinical and socio-demographic characteristics for postoperative survival in stage III colorectal cancer (CRC) patients and develops a 5-year postoperative survival prediction model using machine learning algorithms.MethodsData from 13,855 stage III CRC patients who underwent surgery were extracted from the SEER database. …”
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External validation of the QCovid 2 and 3 risk prediction algorithms for risk of COVID-19 hospitalisation and mortality in adults: a national cohort study in Scotland by Aziz Sheikh, Julia Hippisley-Cox, Chris Robertson, Holly Tibble, Colin R Simpson, Colin McCowan, Igor Rudan, Adeniyi Francis Fagbamigbe, Steven Kerr, Tristan Millington, Karen Jeffrey

“…Objective The QCovid 2 and 3 algorithms are risk prediction tools developed during the second wave of the COVID-19 pandemic that can be used to predict the risk of COVID-19 hospitalisation and mortality, taking vaccination status into account. …”
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Performance evaluation and comparative analysis of different machine learning algorithms in predicting postnatal care utilization: Evidence from the ethiopian demographic and health survey 2016. by Daniel Niguse Mamo, Agmasie Damtew Walle, Eden Ketema Woldekidan, Jibril Bashir Adem, Yosef Haile Gebremariam, Meron Asmamaw Alemayehu, Ermias Bekele Enyew, Shimels Derso Kebede

“…This research aims to evaluate and compare the effectiveness of machine learning algorithms in predicting postnatal care utilization in Ethiopia and to identify the key factors involved. …”
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