Predicting patient outcomes and risk for revision surgery after hip and knee replacement surgery: study protocol for a comparison of modelling approaches using the Swiss National J... by Léonie Hofstetter, Nathalie Schweyckart, Christof Seiler, Christian Brand, Laura C. Rosella, Mazda Farshad, Milo A. Puhan, Cesar A. Hincapié

“…Abstract Background Prediction of postoperative patient-reported outcomes and risk for revision surgery after total hip arthroplasty (THA) or total knee arthroplasty (TKA) can inform clinical decision-making, health resource allocation, and care planning. Machine learning (ML) algorithms are increasingly used as an alternative to traditional logistic regression (LR) prediction, but there is uncertainty about their superiority in overall model performance. …”
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On the Modelling of the Mobile WiMAX (IEEE 802.16e) Uplink Scheduler by Darmawaty Mohd Ali, Kaharudin Dimyati

“…Packet scheduling has drawn a great deal of attention in the field of wireless networks as it plays an important role in distributing shared resources in a network. The process involves allocating the bandwidth among users and determining their transmission order. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…The AI integration in healthcare can revolutionise the industry by improving patient outcomes, optimising resource allocation, and reducing operational costs. …”
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Comprehensive Load Regulation Strategy Considering Outage Risk in Power Tight Balance Scenarios by Shunjiang Wang, Zhongwei Li, Rongmao Wang, Huan Ma

“…Then, orderly consumption power (OCP) is determined by power balance analyzing and flexible resource accessing, reasonably allocated over the subsystems by considering the load types and energy efficiencies, and further specified by components of peak shifting, peak averting and power rationing. …”
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Preventing Health Risks Through Intelligent Medical Appointment Management Using Disease and Attendance Propensity by Fredy Troncoso-Espinosa, Guillermo Latorre-Nunez, Catalina Valenzuela-Nunez, Juan San Martin-Duran

“…Patients scheduled by the intelligent model show higher mean propensities to attend appointments and to develop diseases, ensuring that medical resources are allocated efficiently to those in greatest need. …”
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Dynamic energy consumption monitoring and scheduling for green buildings: A comprehensive approach by Hua Zheng, Pengming Wang

“…The scheduling strategy adopts a dynamic approach based on priority to flexibly allocate energy resources to ensure the coordinated operation of various energy systems in the building. …”
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Modeling Energy Access Challenges in Europe: A Neural Network Approach to Predicting Household Heating Inadequacy Using Macro-Energy Indicators by Monika Kulisz, Justyna Kujawska, Michał Cioch, Wojciech Cel

“…The findings highlight the potential of machine learning to predict the percentage of the population unable to keep their houses adequately warm, enabling policymakers to allocate resources more efficiently and target vulnerable populations. …”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…Abstract The increasing scale of unconventional oil and gas resource development has driven the demand for complex fracturing technologies. …”
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Forecasting dengue in Bangladesh using meteorological variables with a novel feature selection approach by Mahadee Al Mobin

“…The necessity for advanced forecasting mechanisms has never been more critical to enhance the effectiveness of vector control strategies and resource allocations. This study formulates a dynamic data pipeline to forecast dengue incidence based on 13 meteorological variables using a suite of state-of-the-art machine learning models and custom features engineering, achieving an accuracy of 84.02%, marking a substantial improvement over existing studies. …”
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Large Language Model-Assisted Reinforcement Learning for Hybrid Disassembly Line Problem by Xiwang Guo, Chi Jiao, Peng Ji, Jiacun Wang, Shujin Qin, Bin Hu, Liang Qi, Xianming Lang

“…Recycling end-of-life products is essential for reducing environmental impact and promoting resource reuse. In the realm of remanufacturing, researchers are increasingly concentrating on the challenge of the disassembly line balancing problem (DLBP), particularly on how to allocate work tasks effectively to enhance productivity. …”
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Bayesian optimization of hybrid quantum LSTM in a mixed model for precipitation forecasting by Yumin Dong, Huanxin Ding

“…Accurate forecasting is of great significance for reducing the impact of floods, optimizing crop planting plans, rationally allocating water resources, and ensuring traffic safety. …”
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Customer Clustering and Marketing Optimization in Hospitality: A Hybrid Data Mining and Decision-Making Approach from an Emerging Economy by Maryam Deldadehasl, Houra Hajian Karahroodi, Pouya Haddadian Nekah

“…It also provides managers with appropriate tools to allocate resources efficiently. This study extends the traditional Recency, Frequency, and Monetary (RFM) model by incorporating duration, an overlooked dimension of customer engagement. …”
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Petrological controls on the engineering properties of carbonate aggregates through a machine learning approach by Javid Hussain, Tehseen Zafar, Xiaodong Fu, Nafees Ali, Jian Chen, Fabrizio Frontalini, Jabir Hussain, Xiao Lina, George Kontakiotis, Olga Koumoutsakou

“…This approach offers significant advantages in the preliminary assessment of aggregate suitability, contributing to more efficient resource allocation in construction projects.…”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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A Distribution Model for Shared Parking in Residential Zones that Considers the Utilization Rate and the Walking Distance by Wenhui Zhang, Fan Gao, Shurui Sun, Qiuying Yu, Jinjun Tang, Bohang Liu

“…First, managers want to utilize parking resources fully. Therefore, they tend to prioritize the efficient distribution of parking spaces in response to parking demands. …”
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Hierarchical Task Assignment Strategy for Heterogeneous Multi-UAV System in Large-Scale Search and Rescue Scenarios by Jie Chen, Kai Xiao, Kai You, Xianguo Qing, Fang Ye, Qian Sun

“…At last, considering that a few targets cannot be effectively allocated due to UAVs’ limited and unbalanced resources, an auction-based task sharing scheme among UAV teams is presented to guarantee the mission coverage of the multi-UAV system. …”
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Spatio-temporal distribution, prediction and relationship of three major acute cardiovascular events: Out-of-hospital cardiac arrest, ST-elevation myocardial infarction and stroke by Angelo Auricchio, Tommaso Scquizzato, Federico Ravenda, Ruggero Cresta, Stefano Peluso, Maria Luce Caputo, Stefano Tonazzi, Claudio Benvenuti, Antonietta Mira

“…Widespread implementation in clinical practice of prediction algorithms may allow to improve resource allocation, reduce treatment delays, and improve outcomes.…”
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Secure and fast mobility handover scheme for IoMT in 5 G and future 6 G networks by Shayla Islam, S.M. Topazal, Mohammad Kamrul Hasan, Raenu AL Kolandaisamy, Huda Saleh Abbas, Nguyen Vo, Rahul Thakkar, Muhammad Attique Khan, Deepak Gupta, Dina Abdulaziz AlHammadi

“…The predictive algorithm anticipates device movement and pre-allocates resources at the target Base Station (BS), reducing HO latency by 20–30 % in 5 G and up to 40 % in 6 G. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…By analyzing population-level data, AI can identify trends and hotspots of diabetes prevalence, assisting policymakers in resource allocation and the design of targeted interventions. …”
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An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…Abstract Background Metastatic spinal disease often leads to significant morbidity, and accurate prediction of postoperative outcomes can help optimize patient management and resource allocation. The development of such a predictive tool is crucial in clinical decision-making and enhancing patient care. …”
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