Use of machine learning to predict creativity among nurses: a multidisciplinary approach by Rola H. Mudallal, Majd T. Mrayyan, Mohammad Kharabsheh

“…The developed decision support system may be valuable for helping nurse managers evaluate creativity among nurses; this allows for more informed decisions about staff allocation, development, and resource optimization. …”
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Dynamic Load Balancing for Enhanced Network Performance in IoT-Enabled Smart Healthcare With Fog Computing by Mohammed Alaa Ala'anzy, Raiymbek Zhanuzak, Ramis Akhmedov, Nader Mohamed, Jameela Al-Jaroodi

“…To address these limitations, an Optimised Load Balancing (OLB) algorithm is proposed, to allocate workloads effectively across fog nodes and to reduce communication and computational delays. …”
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Genetics of kidney stones and the role of genetic testing in prevention: a guide for urologists by Francesco Pintus, Noemi Giordano, Daniela Francesca Giachino, Giorgia Mandrile

“…This paper reviews the updated evidences in KSD genetics and suggest a diagnostic algorithm aimed to increase the diagnostic rate of genetic stones, allowing a personalized treatment and, in turn, a higher disease-free survival for the patients and a more efficient allocation of resources, analyzing the cost-effectiveness of genetic testing in urolithiasis. …”
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Smart grid stability prediction model using two-way attention based hybrid deep learning and MPSO by Umesh Kumar Lilhore, Surjeet Dalal, Magdalena Radulescu, Marinela Barbulescu

“…In smart grid management, precise stability prediction is a complicated task that adds to the effective allocation of resources with grid stability. Specifically, demand-side management is considered an essential element of the overall Smart Grids system. …”
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The clinical performance of an office-based risk scoring system for fatal cardiovascular diseases in North-East of Iran. by Sadaf G Sepanlou, Reza Malekzadeh, Hossein Poustchi, Maryam Sharafkhah, Saeed Ghodsi, Fatemeh Malekzadeh, Arash Etemadi, Akram Pourshams, Paul D Pharoah, Christian C Abnet, Paul Brennan, Paolo Boffetta, Sanford M Dawsey, Farin Kamangar

“…Risk scoring systems for CVD are needed to prioritize allocation of limited resources. Most of these risk score algorithms have been based on a long array of risk factors including blood markers of lipids. …”
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APPLICATION OF NON-TEST METHODS FOR CHANEL ESTIMATION by M. L. Maslakov, M. S. Smal

“…The problem is currently  pressing  due  to increasing  demands of modern adaptive data  transmission systems to efficient  use of allocated  frequency-time resource  of radio channel. …”
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Navigating the landscape: Unveiling the reflection of AI in the sharing economy through bibliometric-based approach by Veljko Uskoković, Milica Maričić, Aleksandra Dacić-Pilčević, Veljko Jeremić

“…Furthermore, AI optimizes resource allocation and improves matching algorithms on online labour platforms, thereby boosting platform efficiency. …”
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Evaluating accountability, transparency, and bias in AI-assisted healthcare decision- making: a qualitative study of healthcare professionals’ perspectives in the UK by Saoudi CE Nouis, Victoria Uren, Srushti Jariwala

“…Results Participants reported notable gains in diagnostic efficiency and resource allocation, underscoring AI’s potential to reduce turnaround times for routine tests and enhance detection of abnormalities. …”
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OliveTreeCrownsDb: A high-resolution UAV dataset for detection and segmentation in agricultural computer visionMendeley Data by Youness Hnida, Mohamed Adnane Mahraz, Ali Achebour, Ali Yahyaouy, Jamal Riffi, Hamid Tairi

“…It facilitates the development of innovative algorithms to optimize resource allocation and improve crop management. …”
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From 6G to <i>SeaX-G</i>: Integrated 6G TN/NTN for AI-Assisted Maritime Communications—Architecture, Enablers, and Optimization Problems by Anastasios Giannopoulos, Panagiotis Gkonis, Alexandros Kalafatelis, Nikolaos Nomikos, Sotirios Spantideas, Panagiotis Trakadas, Theodoros Syriopoulos

“…Finally, we propose a set of resource optimization scenarios, including dynamic spectrum allocation, energy-efficient communications and edge offloading in MCNs, and discuss how AI/ML and learning-based methods can offer scalable, adaptive solutions. …”
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Risk factors for tuberculosis treatment outcomes: a statistical learning-based exploration using the SINAN database with incomplete observations by Nguyen Ky Phat, Yoonah Lee, Dinh Hoa Vu, Nguyen Phuoc Long, Seongoh Park

“…Abstract Background Understanding early predictors of treatment outcomes allows better outcome prediction and resource allocation for efficient tuberculosis (TB) management. …”
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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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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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