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741
Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper
Published 2025“…Future research should focus on refining algorithms, ensuring real‐time adaptability, addressing ethical considerations, evaluating long‐term patient outcomes, fostering cooperative systems, and integrating relevant data and policies within the healthcare framework.…”
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742
Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications
Published 2025“…</p><h3>Materials and methods</h3><p dir="ltr">An ensemble<u> species distribution modelling </u>approach, integrating regression-based and machine-learning algorithms (GLM, GBM, RF, MaxEnt), was used to project habitat suitability (Current time and by 2050, 2070, and 2090). …”
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743
Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study
Published 2024“…</p><h3>Objective</h3><p dir="ltr">In this paper, we propose a machine learning–based approach for identifying research gaps through the analysis of scientific literature. We used the COVID-19 pandemic as a case study.</p><h3>Methods</h3><p dir="ltr">We conducted an analysis to identify research gaps in COVID-19 literature using the COVID-19 Open Research (CORD-19) data set, which comprises 1,121,433 papers related to the COVID-19 pandemic. …”
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744
The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns
Published 2024“…This dissertation explores the impact of AI on decision-making in educational management, focusing on the benefits, risks, and ethical concerns associated with its use. AI technologies offer significant advantages, such as data-driven insights, improved efficiency, and enhanced predictive capabilities, which can support educational leaders in making more informed decisions. …”
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745
Reconstruction and simulation of neocortical microcircuitry
Published 2015“…We present a first-draft digital reconstruction of the microcircuitry of somatosensory cortex of juvenile rat. The reconstruction uses cellular and synaptic organizing principles to algorithmically reconstruct detailed anatomy and physiology from sparse experimental data. …”
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746
Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
Published 2024“…Furthermore, this study also focuses on different Machine learning algorithms that are used to secure wireless sensor networks. …”
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747
Industrial Internet of Things enabled technologies, challenges, and future directions
Published 2023“…This paper explores IIoT-enabled technologies and infrastructure, their role in global industrial growth, applications, challenges, and future directions. IIoT applications use the intelligence of things to solve industrial problems like supply chain mismanagement, data privacy risks, a weak cloud strategy, cost containment, and others. …”
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748
Scatter search technique for exam timetabling
Published 2011“…We evaluate our suggested technique on real-world university data and compare our results with the registrar’s manual timetable in addition to the timetables of other heuristic optimization algorithms. …”
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749
SemIndex: Semantic-Aware Inverted Index
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conferenceObject -
750
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751
Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning
Published 2025“…This article provides an updated review of the cutting-edge machine learning and data-driven techniques used for PGP in networked PSs. …”
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752
Industrial Internet of Things enabled technologies, challenges, and future directions
Published 2023“…This paper explores IIoT-enabled technologies and infrastructure, their role in global industrial growth, applications, challenges, and future directions. IIoT applications use the intelligence of things to solve industrial problems like supply chain mismanagement, data privacy risks, a weak cloud strategy, cost containment, and others. …”
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753
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754
A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies
Published 2024“…Study selection, quality assessment, and data extraction were performed independently by four authors. …”
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755
Precision nutrition: A systematic literature review
Published 2021“…Therefore, we carried out a Systematic Literature Review (SLR) to provide an overview of where and how machine learning has been used in Precision Nutrition from various aspects, what such machine learning models use as input features, what the availability status of the data used in the literature is, and how the models are evaluated. …”
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756
Engineering the advances of the artificial neural networks (ANNs) for the security requirements of Internet of Things: a systematic review
Published 2023“…In this question, we also determined the various models, frameworks, techniques and algorithms suggested by ANNs for the security advancements of IoT. …”
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757
Iterative Methods for the Solution of a Steady State Biofilter Model
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doctoralThesis -
758
Software-Defined-Networking-Based One-versus-Rest Strategy for Detecting and Mitigating Distributed Denial-of-Service Attacks in Smart Home Internet of Things Devices
Published 2024“…We conducted a comparative analysis of various models and algorithms used in the related works. The results indicated that our proposed approach outperforms others, showcasing its effectiveness in both detecting and mitigating DDoS attacks within SDNs. …”
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759
Making progress with the automation of systematic reviews: principles of the International Collaboration for the Automation of Systematic Reviews (ICASR)
Published 2018“…Recent advances in natural language processing, text mining and machine learning have produced new algorithms that can accurately mimic human endeavour in systematic review activity, faster and more cheaply. …”
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760
Towards secure private and trustworthy human-centric embedded machine learning: An emotion-aware facial recognition case study
Published 2023“…Since the success of AI is to be measured ultimately in terms of how it benefits human beings, and that the data driving the deep learning-based edge AI algorithms are intricately and intimately tied to humans, it is important to look at these AI technologies through a human-centric lens. …”