Ethical dimensions of artificial intelligence in graphic design: challenges, opportunities and the future of creative practice by Sandra Dedijer, Nemanja Kašiković, Magdolna Pál, Ivana Jurič, Živko Pavlović, Saša Petrović, Gala Golubović

“…The ethical use of AI in graphic design spans multiple dimensions: algorithmic bias, user privacy, transparency of sources and influence, and questions of ownership and intellectual property. …”
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Proactive detection of cyber-physical grid attacks: A pre-attack phase identification and analysis using anomaly-based machine learning models by Shaharier Kabir, Nasif Hannan, Abu Shufian, Md Saniat Rahman Zishan

“…Several unsupervised learning algorithms were applied to time series data simulating normal operations and attack scenarios. …”
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Unboxing Tree ensembles for interpretability: A hierarchical visualization tool and a multivariate optimal re-built tree by Giulia Di Teodoro, Marta Monaci, Laura Palagi

“…The interpretability of models has become a crucial issue in Machine Learning because of algorithmic decisions' growing impact on real-world applications. …”
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Software Defect Prediction Using Deep Q-Learning Network-Based Feature Extraction by Qinhe Zhang, Jiachen Zhang, Tie Feng, Jialang Xue, Xinxin Zhu, Ningyang Zhu, Zhiheng Li

“…Moreover, without proper feature reduction, the interpretability and generalization ability of machine learning models in SDP may be compromised, hindering their practical utility in diverse software development environments. …”
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Fostemsavir resistance in clinical context: a narrative review by Jonathan M. Schapiro, Rolf Kaiser, Mark Krystal, Chris M. Parry, Allan R. Tenorio, Eugene Stewart, Bruce Gilliam, Margaret Gartland, Andrew Clark, Jose R. Castillo-Mancilla

“…Due to these factors and limited phenotypic clinical data, thus far, no relevant phenotypic cutoff or genotypic algorithms have been derived that reliably predict response to fostemsavir-based therapy in individuals who are HTE; therefore, pre-treatment temsavir resistance testing may be of limited benefit. …”
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The Current Role and Prospects of Electrophysiological Research Methods in Ophthalmology. Literature Review by V. N. Kazajkin, V. O. Ponomarev, A. V. Lizunov, A. E. Zhdanov, A. Yu. Dolganov, V. I. Borisov

“…This leaves the possibility and the need for the study, optimization and algorithmization of the assessment data of the differentiated criteria inherent for a particular ocular pathology. …”
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Advanced Artificial Intelligence Technologies Transforming Contemporary Pharmaceutical Research by Parveen Kumar, Benu Chaudhary, Preeti Arya, Rupali Chauhan, Sushma Devi, Punit B. Parejiya, Madan Mohan Gupta

“…This technique includes data collection, effective data usage system development, conclusion illustration, and arrangements. Analysis algorithms that are learning to mimic human cognitive activities are the most widespread application of AI. …”
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A Survey on Video Compression Optimization Techniques for Accuracy Enhancement in Video Analytics Applications (VAPs) by Kholidiyah Masykuroh, Hendrawan, Eueung Mulyana, Farhan Krishna

“…We examine traditional compression algorithms, machine learning-based approaches, dynamic parameter adjustment strategies, and hybrid models, each offering unique strengths and limitations. …”
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Global Navigation Satellite System Positioning Under Interference Conditions by Sebastian Cikovsky, Milan Dzunda

“…This paper’s contribution is the creation of algorithms for processing GNSS signals under interference conditions based on the Savitzky-Golay filter and neural network. …”
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The impact of artificial intelligence on human resource management practices: An investigation by Thandukwazi R. Ncube, Kusangiphila K. Sishi, Jane P. Skinner

“…These include potential biases within AI algorithms, concerns about data privacy and over-surveillance of employees, along with exacerbating the ‘digital divide’ between those with access to technology and those without. …”
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Predicting major amputation risk in diabetic foot ulcers using comparative machine learning models for enhanced clinical decision-making by Zixuan Liu, Dehua Wei, Jiangning Wang, Lei Gao

“…Abstract It is to develop a predictive model utilizing machine learning techniques to promptly identify patients with diabetic foot ulcers (DFU) who may require major amputation upon their initial admission. …”
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Blood-based biomarkers in patients with non-small cell lung cancer treated with immune checkpoint blockade by Yo-Ting Tsai, Jeffrey Schlom, Renee N. Donahue

“…Integration of multiple blood-based biomarkers into comprehensive panels or algorithms also has the potential to enhance predictive accuracy. …”
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Adverse childhood experiences: terms, concepts, and study methods by Diana S. Shumskaia, Anna V. Trusova, Alexander O. Kibitov

“…However, to date, there is no unique and universally accepted approach to assessment of ACE, which may lead to controversy and low reproducibility of results.The purpose of this review is to examine and compare various methods of assessing and interpreting of ACE in order to identify optimal research algorithms within the current interpretation of the biopsychosocial model in psychiatry.This article reviews current terms, concepts, and methods of studying ACE. …”
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Electroencephalographic monitoring in detection and prediction of delayed cerebral ischemia due to non-traumatic subarachnoid hemorrhage by I. V. Okuneva, M. V. Sinkin, A. I. Evdokimov, A. V. Prirodov

“…Future studies should be aimed at clarifying and validating the most informative DCI biomarkers including while recording EEG with intracranial electrodes that may contribute to development of automated algorithms for DCI detection.…”
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Research Status and Progress of Acoustic Fire Extinguishing Technology by Xinyue Shi, Zhaojun Tian, Yi Lu, Qing Ye

“…Future advancements require breakthroughs in acoustic metamaterials, the integration of intelligent algorithms, and the collaborative optimization of multi-technology systems to facilitate the transition of acoustic wave-based fire suppression from laboratory settings to real-world industrial firefighting applications. …”
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TECTONOPHYSICAL ZONING OF ACTIVE FAULTS OF THE BAIKAL RIFT SYSTEM by Yu. L. Rebetsky, A. A. Dobrynina, V. A. Sankov

“…The second important element of fault zoning was electronic maps of active faults of Eurasia hosted on the GIN RAS sever. Within the algorithmic framework for Rebetsky’s method of cataclastic analysis, both of these datasets allowed calculating the Coulomb stresses for the segments of the BRS faults. …”
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Fine-Tuned Machine Learning Classifiers for Diagnosing Parkinson’s Disease Using Vocal Characteristics: A Comparative Analysis by Mehmet Meral, Ferdi Ozbilgin, Fatih Durmus

“…This study seeks to assess the effectiveness of machine learning algorithms optimized to classify PD based on vocal characteristics to serve as a non-invasive and easily accessible diagnostic tool. …”
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BAMHealthCloud: A biometric authentication and data management system for healthcare data in cloud by Kashish A. Shakil, Farhana J. Zareen, Mansaf Alam, Suraiya Jabin

“…The healthcare data management system records patient’s data in different formats such as text, numeric, pictures and videos leading to data which is big and unstructured. Also, hospitals may have several branches in different geographical locations. …”
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Neurotechnological Approaches to Cognitive Rehabilitation in Mild Cognitive Impairment: A Systematic Review of Neuromodulation, EEG, Virtual Reality, and Emerging AI Applications by Evgenia Gkintoni, Stephanos P. Vassilopoulos, Georgios Nikolaou, Apostolos Vantarakis

“…<i>Background/Objectives:</i> Mild Cognitive Impairment (MCI) represents a clinical syndrome characterized by cognitive decline greater than expected for an individual’s age and education level but not severe enough to significantly interfere with daily activities, with variable trajectories that may remain stable, progress to dementia, or occasionally revert to normal cognition. …”
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Diagnostic models for sepsis-associated encephalopathy: a comprehensive systematic review and meta-analysis by Tengfei Zhou, Tengfei Zhou, Xinming Tian, Wei Wang, Zhe Chu

“…A total of 29 predictive models were developed, comprising 10 optimal models, primarily utilizing logistic regression or machine learning algorithms. The combined AUC of the five logistic regression models was 0.85 (95% CI 0.77–0.93), exhibiting substantial heterogeneity (I2 = 91.8%). …”
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