Artificial Intelligence in Digital Marketing: Towards an Analytical Framework for Revealing and Mitigating Bias by Catherine Reed, Martin Wynn, Robin Bown

“…Traditional AI centres on supervised learning algorithms to support and enable the application of data rules, predictive functionality and other AI-based features. …”
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Data-driven modelling of a commercial cold storage system using subspace system identification by Adesola Temitope Bankole, Muhammed Bashir Mu’azu, Habeeb Bello-Salau, Zaharuddeen Haruna

“…The proposed model is stable, robust and suitable for testing linear control algorithms.…”
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WDS-YOLO: A Marine Benthos Detection Model Fusing Wavelet Convolution and Deformable Attention by Jiahui Qian, Ming Chen

“…Furthermore, it outperformed several mainstream underwater object detection algorithms, achieving a detection speed of 104.5 fps. …”
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Identification of thyroid cancer biomarkers using WGCNA and machine learning by Gaofeng Hu, Wenyuan Niu, Jiaming Ge, Jie Xuan, Yanyang Liu, Mengjia Li, Huize Shen, Shang Ma, Yuanqiang Li, Qinglin Li

“…DEGs were analyzed using DESeq2, and WGCNA identified gene modules associated with TC. Machine learning algorithms (XGBoost, LASSO, RF) identified key biomarkers, with ROC and AUC > 0.95 indicating strong diagnostic performance. …”
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Hydrocephalus: Molecular and Neuroimaging Biomarkers in Diagnosis and Management by Andrada-Iasmina Roşu, Diana Andrei, Laura Andreea Ghenciu, Sorin Lucian Bolintineanu

“…Parallel to molecular advances, neuroimaging techniques, ranging from classic markers like Evans’ index to advanced modalities such as diffusion tensor imaging (DTI), arterial spin labeling (ASL), and glymphatic MRI, provide functional perspectives on hydrocephalus diagnosis and management, while artificial intelligence may further enhance diagnostic algorithms. …”
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Rethinking Technological Investment and Cost-Benefit: A Software Requirements Dependency Extraction Case Study by Gouri Ginde, Guenther Ruhe, Chad Saunders

“…It can substantially improve the efficiency and effectiveness of organizations. While various methods and techniques exist, all of them have strengths and weaknesses under varying scenarios and contexts. …”
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Machine learning-based prediction of physical parameters in heterogeneous carbonate reservoirs using well log data by Fuyong Wang, Xianmu Hou

“…Six machine learning algorithms are utilized: support vector machine (SVM), backpropagation (BP) neural network, gaussian process regression (GPR), extreme gradient boosting (XGBoost), K-nearest neighbor (KNN), and random forest (RF). …”
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Expedited re-design of multi-band passive microwave circuits using orthogonal scaling directions and gradient-based tuning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…In particular, the employment of a given passive structure in a different application area often requires re-adjustment of the operating frequencies/bands while maintaining top performance. Achieving this necessitates the utilization of numerical optimization methods. …”
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MODEL OF DATA TRAFFIC QOS FAST REROUTING IN INFOCOMMUNICATION NETWORKS by Oleksandr Lemeshko, Maryna Yevdokymenko, Oleksandra Yeremenko

“…The application of this solution contributes to the optimal use of the available network resource while providing the specified level of Quality of Service in terms of bandwidth and probability of packet loss along both the primary and backup routes in the case of a failure of the infocommunication network elements. …”
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AI in biomedical science: innovations, challenges, and ethical perspectives by Aynur Aliyeva

“…Key technologies such as generative AI platforms, machine learning algorithms, and mobile-based auditory training systems are highlighted. …”
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Neo-antigen specific cancer vaccines for acute lymphoblastic leukemia—challenges, opportunities, and future directions by Victoria Bloch Blytt Sandstad, Signe Modvig, Morten Orebo Holmström

“…Abstract Acute lymphoblastic leukemia (ALL) is the most common pediatric malignancy, with standard treatment consisting of intensive chemotherapy and corticosteroids. While curative in most cases, this regimen leads to significant toxicity and long-term sequelae. …”
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Water tank and swimming pool detection based on remote sensing and deep learning: Relationship with socioeconomic level and applications in dengue control. by Higor Souza Cunha, Brenda Santana Sclauser, Pedro Fonseca Wildemberg, Eduardo Augusto Militão Fernandes, Jefersson Alex Dos Santos, Mariana de Oliveira Lage, Camila Lorenz, Gerson Laurindo Barbosa, José Alberto Quintanilha, Francisco Chiaravalloti-Neto

“…Thus, we found that regions with low socioeconomic status had more exposed water tanks, while regions with high socioeconomic levels had more exposed pools. …”
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Optimizing deep learning for accurate blood cell classification: A study on stain normalization and fine-tuning techniques by Mohammed Tareq Mutar, Jaffar Nouri Alalsaidissa, Mustafa Majid Hameed, Ali Almothaffar

“…BACKGROUND: Deep learning’s role in blood film screening is expanding, with recent advancements including algorithms for the automated detection of sickle cell anemia, malaria, and leukemia using smartphone images. …”
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Balancing Ethics and Privacy in the Use of Artificial Intelligence in Institutions of Higher Learning: A Framework for Responsive AI Systems by Belinda Ndlovu, Kudakwashe Maguraushe

“…Artificial Intelligence (AI) is swiftly revolutionising higher education, presenting substantial prospects for innovation while concurrently evoking ethical and privacy concerns. …”
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Porous Models for Enhanced Representation of Saturated Curly Hairs: Simulation and Learning by Jong-Hyun Kim, Jung Lee

“…Additionally, we propose to extend the learning representation solver through both numerical simulation algorithms and AI-based approaches.…”
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Unsupervised Action Anticipation Through Action Cluster Prediction by Jiuxu Chen, Nupur Thakur, Sachin Chhabra, Baoxin Li

“…However, the inherent challenge lies in deciphering the complex spatial-temporal dynamics inherent in typical video feeds. While existing works excel in constrained settings with fine-grained action ground-truth labels, the general unavailability of such labeling at the frame level poses a significant hurdle. …”
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A Systematic Literature Review of Machine Learning-Based Personality Trait Detection Using Electroencephalographic Data by Celina Rieck, Pascal Penava, Ricardo Buettner

“…The integration of machine and deep learning algorithms has improved automated trait classification but the comparative reliability of these approaches remains unclear. …”
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REDalign: accurate RNA structural alignment using residual encoder-decoder network by Chun-Chi Chen, Yi-Ming Chan, Hyundoo Jeong

“…Abstract Background RNA secondary structural alignment serves as a foundational procedure in identifying conserved structural motifs among RNA sequences, crucially advancing our understanding of novel RNAs via comparative genomic analysis. While various computational strategies for RNA structural alignment exist, they often come with high computational complexity. …”
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Enhancing SQL Learning: Gamified tutorials and flipped classroom synergy by Sandor Kiraly, Tamas Balla, Dora Kiraly, Geoffrey Vaughan

“…Teaching students to think algorithmically is a common goal for school educators; however, SQL's declarative nature demands a distinct approach to problem-solving. …”
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Deep Learning in Power Systems: A Bibliometric Analysis and Future Trends by Seyed Mahdi Miraftabzadeh, Andrea Di Martino, Michela Longo, Dario Zaninelli

“…Advancements in deep learning enable sophisticated algorithms to learn from vast data sets, driving innovation and efficiency in power systems. …”
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