Single-Cell Transcriptome Analysis Revealed Heterogeneity and Identified Novel Therapeutic Targets for Breast Cancer Subtypes by Radhakrishnan Vishnubalaji (3563306)

“…In the current study, we employed computational algorithms to decipher the cellular composition of estrogen receptor-positive (ER⁺), HER2⁺, ER⁺HER2⁺, and triple-negative BC (TNBC) subtypes from a total of 49,899 single cells’ publicly available transcriptomic data derived from 26 BC patients. …”

Teachers' Perceptions of the Role of Artificial Intelligence in Facilitating Inclusive Practices for Students with Special Educational Needs and Disabilities: A Case Study in a Pri... by BACHIR, HIBAH AHMAD

“…Findings referred these barriers to limited teacher training, technological accessibility, and data privacy concerns, as well as ethical biases in AI algorithms. …”
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Artificial intelligence-enhanced electrocardiography for accurate diagnosis and management of cardiovascular diseases by Muhammad Ali Muzammil (17910611)

“…To guarantee a safe and successful deployment in clinical practice, the use of AI in cardiology must be done with a thorough understanding of the algorithms and their limits. …”

Optimising Nurse–Patient Assignments: The Impact of Machine Learning Model on Care Dynamics—Discursive Paper by Mutaz I. Othman (21186827)

“…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.…”

Impacts of climate change on the global spread and habitat suitability of <i>Coxiella burnetii</i>: Future projections and public health implications by Abdallah Falah Mohammad Aldwekat (22457821)

“…</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). …”

DeepRaman: Implementing surface-enhanced Raman scattering together with cutting-edge machine learning for the differentiation and classification of bacterial endotoxins by Samir Brahim, Belhaouari

“…ConclusionWe present the effectiveness of DeepRaman, an innovative architecture inspired by the Progressive Fourier Transform and integrated with the scalogram transformation method, in classifying raw SERS Raman spectral data from biological specimens with unparalleled accuracy relative to conventional machine learning algorithms. …”
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Machine Learning–Based Approach for Identifying Research Gaps: COVID-19 as a Case Study by Alaa Abd-alrazaq (17058018)

“…</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. …”

The Impact of AI on Decision-Making in Educational Management: Benefits, Risks, and Ethical Concerns by JA’AROUN, WAED YOUSEF

“…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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Cooperative Caching Policy in Fog Computing for Connected Vehicles by Ghazleh, Ali

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Reconstruction and simulation of neocortical microcircuitry by Khazen, Georges

“…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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Industrial Internet of Things enabled technologies, challenges, and future directions by Shams Forruque, Ahmed

“…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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Scatter search technique for exam timetabling by Mansour, Nashat

“…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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SemIndex: Semantic-Aware Inverted Index by Chbeir, Richard

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WiMAX Models for the Smart Grid by Al-Omar, Ban Abdul Elah

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Advancing Coherent Power Grid Partitioning: A Review Embracing Machine and Deep Learning by Mohamed Massaoudi (16888710)

“…This article provides an updated review of the cutting-edge machine learning and data-driven techniques used for PGP in networked PSs. …”

Industrial Internet of Things enabled technologies, challenges, and future directions by Shams Forruque Ahmed (16517712)

“…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. …”

Classification automatique et stratégie d'annotation appliquées à un concept philosophique: la dimension psychologique du concept de LANGAGE dans l'oeuvre de Bergson 1 by Alrahabi, Al Moatasem

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A systematic review of recent advances in the application of machine learning in membrane-based gas separation technologies by Farideh Abdollahi (22303153)

“…Study selection, quality assessment, and data extraction were performed independently by four authors. …”

Precision nutrition: A systematic literature review by Daniel Kirk (17302798)

“…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. …”

Machine learning for predicting outcomes of transcatheter aortic valve implantation: A systematic review by Ruba, Sulaiman

“…MethodsPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline was adapted for searching the PubMed and Scopus databases on ML use in TAVI outcomes prediction. Once the studies that meet the inclusion criteria were identified, data from these studies were retrieved and were further examined. 17 parameters relevant to TAVI outcomes were carefully identified for assessing the quality of the included studies. …”
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