Optimising test intervals for individuals with type 2 diabetes: A machine learning approach. by Sasja Maria Pedersen, Nicolai Damslund, Trine Kjær, Kim Rose Olsen

“…<h4>Objective</h4>To demonstrate the potential of ML to guide resource allocation and tailored disease management, this study aims to predict the optimal testing interval for monitoring blood glucose (HbA1c) for patients with Type 2 Diabetes (T2D). …”
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Responsible artificial intelligence in public health: a Delphi study on risk communication, community engagement and infodemic management by Keyrellous Adib, David Novillo-Ortiz, Ben Duncan, Daniela Mahl, Mike S Schäfer, Stefan Adrian Voinea, Cristiana Salvi

“…Prioritised actions ranged from regulatory measures, resource allocation and feedback loops to capacity building, public trust initiatives and educational training.Conclusion To responsibly navigate the multifaceted opportunities, challenges and risks of AI for RCCE-IM in public health emergencies, clear guiding principles, ongoing critical evaluation and training as well as societal collaboration across countries are needed.…”
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Fuzzy Clustering Based on Activity Sequence and Cycle Time in Process Mining by Onur Dogan, Hunaıda Avvad

“…Ultimately, the framework enhances process mining by offering detailed insights for analyzing operational inefficiencies, bottlenecks, and resource allocation mismatches, providing substantial real-world benefits for industries that demand effective process improvement.…”
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Hydropneumatic storage methodology towards a new era of hybrid energy system's efficiency and flexibility by JoaoS.T. Coelho, Modesto Pérez-Sánchez, Oscar E. Coronado-Hernández, Mohsen Besharat, Rui-Lin Feng, Elias Tasca, Ling Zhou, Helena M. Ramos

“…The optimization of hybrid systems through Solver and Python algorithms with various objective functions enables optimal design choices tailored to specific needs such as drinking water supply, irrigation, or industrial processes. …”
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Information-guided adaptive learning approach for active surveillance of infectious diseases by Qi Tan, Chenyang Zhang, Jiwen Xia, Ruiqi Wang, Lian Zhou, Zhanwei Du, Benyun Shi

“…Based on a probabilistic model, we evaluate the information gain of monitoring a spatio-temporal target and design a greedy selection algorithm for monitoring targets selection. Moreover, we integrate two major surveillance objectives, i.e., informativeness and coverage, in the monitoring target selection. …”
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Machine learning-based academic performance prediction with explainability for enhanced decision-making in educational institutions by Wesam Ahmed, Mudasir Ahmad Wani, Pawel Plawiak, Souham Meshoul, Amena Mahmoud, Mohamed Hammad

“…Abstract Education is crucial for the growth of effective life skills and the allocation of needed resources. Higher education institutions are adopting advanced technologies, such as artificial intelligence (AI), to enhance traditional teaching methods. …”
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Joint Encryption and Optimization for 6G MEC-Enabled IoT Networks by Manzoor Ahmed, Wali Ullah Khan, Fatma S. Alrayes, Yahia Said, Ali M. Al-Sharafi, Mi-Hye Kim, Khongorzul Dashdondov, Inam Ullah

“…An optimization algorithm is introduced to address these challenges by jointly allocating resources, thereby optimizing throughput, conserving energy, and meeting latency benchmarks through dynamic system adaptation. …”
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Advances in Deep Learning Applications for Plant Disease and Pest Detection: A Review by Shaohua Wang, Dachuan Xu, Haojian Liang, Yongqing Bai, Xiao Li, Junyuan Zhou, Cheng Su, Wenyu Wei

“…To address these challenges, deep learning technologies have emerged as a promising solution for the accurate and timely identification of plant diseases and pests, thereby reducing crop losses and optimizing agricultural resource allocation. By leveraging its advantages in image processing, deep learning technology has significantly enhanced the accuracy of plant disease and pest detection and identification. …”
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Predicting Hospitalization Length in Geriatric Patients Using Artificial Intelligence and Radiomics by Lorenzo Fantechi, Federico Barbarossa, Sara Cecchini, Lorenzo Zoppi, Giulio Amabili, Mirko Di Rosa, Enrico Paci, Daniela Fornarelli, Anna Rita Bonfigli, Fabrizia Lattanzio, Elvira Maranesi, Roberta Bevilacqua

“…(1) Background: Predicting hospitalization length for COVID-19 patients is crucial for optimizing resource allocation and patient management. Radiomics, combined with machine learning (ML), offers a promising approach by extracting quantitative imaging features from CT scans. …”
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Artificial intelligence in project management: A bibliometric analysis by Nurkhat Ibadildin, Zhaxat Kenzhin, Gaukhar Yeshenkulova, Rymkul Ismailova, Assel Nurguzhina, Samalgul Nassanbekova, Aiman Kadyrova

“…The analysis maps the evolution of AI-driven project management practices, focusing on resource allocation, risk management, and scheduling optimization. …”
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Next-Gen UAV-Satellite Communications: AI Innovations and Future Prospects by Sherief Hashima, Ahmad Gendia, Kohei Hatano, Osamu Muta, Mostafa S. Nada, Ehab Mahmoud Mohamed

“…Furthermore, it includes a case study demonstrating the effectiveness of multi-armed bandit (MAB) algorithms in optimizing resource allocation and decision-making processes for UAV-low Earth orbit (LEO) satellite communication scenarios, showcasing significant improvements in network performance. …”
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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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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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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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Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling by Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong, Deshun Zhang, Jing Li, Manqin Yao, Wei Yong, Mengjia Li, Yujie Huang

“…Accordingly, the proposed model synchronizes Type II peak-hour throughput with Type I off-peak experiential depth using dynamic path allocation algorithms. This study underscores the strong spatial guidance mechanisms of Xishu Gardens, supporting tourism management and heritage conservation.…”
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Performance Assessment of a Rehabilitation Transportation Reservation Matching Service with Market Design Mechanisms by Chen Yu Lan, Chih Peng Chu, Cheng Chieh (Frank) Chen

“…This study applies the market design theory to match the rehabilitation buses with the requests of patients, so as to improve resource utilization efficiency in rural areas. The developed market design mechanisms aim to allocate resources to those who need them most in a matching manner, by using the deferred acceptance algorithm and the top trading cycle approach. …”
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Clinical prediction model for MODY type diabetes mellitus in children by D. N. Laptev, E. A. Sechko, E. M. Romanenkova, I. A. Eremina, O. B. Bezlepkina, V. A. Peterkova, N. G. Mokrysheva

“…The use of the developed model in clinical practice will assist in the selection of patients for diagnostic genetic testing for MODY, which will allow for the efficient allocation of healthcare resources, the selection of personalized treatment and patient monitoring.…”
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Deep reinforcement learning for multi-objective location optimization of onshore wind power stations: a case study of Guangdong Province, China by Yanna Gao, Hong Dong, Liujun Hu, Fanhong Zeng, Yuqun Gao, Zhuonan Huang, Shaohua Wang, Shaohua Wang

“…IntroductionWind energy development faces challenges such as low utilization of wind resources, underdevelopment of suitable areas, and imbalanced electricity demand coverage. …”
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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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Implications of machine learning techniques for prediction of motor health disorders in Saudi Arabia by Ehab M. Almetwally, I. Elbatal, Mohammed Elgarhy, Amr R. Kamel

“…This system is an efficient tool that properly detects and diagnoses a variety of motor impairment problems using ML algorithms. Decisions are made easier and social health care is improved with the help of this system because timely interventions are implemented, patient outcomes are improved, and resource allocation is optimized.…”
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