THE IMPACT OF ARTIFICIAL INTELLIGENCE ON THE DEVELOPMENT OF PREDICTIVE COMPETENCE IN MODERN SPECIALISTS by Viacheslav Osadchyi, Maksym Pavlenko, Liliia Pavlenko, Oleksii Sysoiev, Vladyslav Kruglyk

“…Maximising its benefits while mitigating associated risks requires a proactive, critical, and adaptive attitude from professionals and educators alike. …”
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DYNAMICS OF MMP-8, SRANKL, AND OSTEOCALCIN CONCENTRATIONS IN THE ORAL FLUID OF PATIENTS WITH SECONDARY EDENTULISM AND AFTER PROSTHETIC TREATMENT by R.V. Tsynkush, O.V. Voznyi

“…The predominance of resorptive processes over bone formation in the alveolar ridge area can be the main cause of premature tooth loss, while inflammatory changes in the periodontal tissues accelerate disease progression. …”
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Bioinformatic Analysis of Apoptosis-Related Genes in Preeclampsia Using Public Transcriptomic and Single-Cell RNA Sequencing Datasets by Liu L, Li X, Yang H, Xu F, Dong X

“…We used scRNA-seq and differential expression analysis, combined with five algorithms from the CytoHubba plugin, to identify ARGs as PE biomarkers. …”
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Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices? by Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith

“…Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. …”
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Slip and tractive efficiency of an electric tractor with a 4WID E-axle system by SeungYun Baek, HyeonHo Jeon, CheolGyu Park, YongJoo Kim

“…The primary findings of this study identify the appropriate slip range and provide fundamental data for developing slip control algorithms for the 4WID E-axle system. Future research will focus on experimental validation and development of control algorithms based on the main results.…”
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Dynamic Updating the Three-Way Regions for the Optimal Rules by Xiaohua Wei, Jiangang Ye, Jin Qian, Qiaowen Deng

“…How to acquire the optimal rules from dynamic data while ensuring efficiency becomes an important challenge. …”
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Television in and After the Archive: Catalogues, Databases, Interfaces and Other Ways to Organize Audiovisual Records by Giulia Taurino, Georgia Aitaki

“…Significant attention is given to the technocultural transformation of the archival work in light of digital and algorithmic practices, emphasizing how these innovations contribute to the making of cultural identities and collective memory while also raising questions on the circulation of television content after its initial broadcasting lifecycle. …”
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5G OFDM channel estimation method based on complex-valued generative adversarial network by LU Yuanzhi, WEI Xianglin, YU Long, YAO Changhua

“…Channel estimation methods based on least square (LS) and minimum mean square error (MMSE) effectively utilize the system’s sparsity, but LS algorithms face low computational precision, while MMSE algorithms suffer from high computational complexity. …”
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A synthesis method for zero-sum mean-payoff asynchronous probabilistic games by Wei Zhao, Wanwei Liu, Zhiming Liu, Tiexin Wang

“…Next, two symbolic algorithms running in polynomial time are proposed to calculate the expected mean payoffs, and both algorithms adopt uniform random strategies. …”
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Role of artificial intelligence in medical radiology and imaging by Mohd Arfat, T. K. Nisha, Sapna Sahu, Mohd Rashid

“…Adopting deep learning algorithms has significantly advanced image analysis and disease detection. …”
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Developing a Model to Predict the Effectiveness of Vaccination on Mortality Caused by COVID-19 by Malihe Niksirat, Javad Tayyebi, Seyedeh Fatemeh Javadi, Adrian Marius Deaconu

“…Machine learning (ML) algorithms offer promising tools for predicting vaccine effectiveness and aiding public health decisions. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Bayesian causal discovery provides a principled framework for modeling observational data, generating posterior distributions that best represent the underlying structure. While recent algorithms offer efficient and accurate structure learning, integrating experiment design can further enhance predictive performance. …”
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Imitating a Safe Human Driver Behaviour in Roundabouts Through Deep Learning by A. S. J. Cervera, F. J. Alonso, F. S. García, A. D. Alvarez

“…Roundabouts provide safe and fast circulation as well as many environmental advantages, but drivers adopting unsafe behaviours while circulating through them may cause safety issues, provoking accidents. …”
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Multistable Physical Neural Networks by Ben‐Haim Eran, Givli Sefi, Or Yizhar, Gat D. Amir

“…Building on these maps, both global and local algorithms for training multistable PNNs are implemented. …”
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A feature selection method with feature ranking using genetic programming by Guopeng Liu, Jianbin Ma, Tongle Hu, Xiaoying Gao

“…Feature selection based on evolutionary computation (EC) algorithms can often achieve better classification performance because of their global search ability. …”
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Robust Cross-Validation of Predictive Models Used in Credit Default Risk by Jose Vicente Alonso, Lorenzo Escot

“…Model validation is a challenging Machine Learning task, usually more difficult for consumer credit default models because of the availability of small datasets, the modeling of low-frequency events (imbalanced data), and the bias in the explanatory variables induced by the train/test sets split of the validation techniques (covariate shift). While many methodologies have been developed, cross-validation is perhaps the most widely accepted, often being part of the model development process by optimizing the hyperparameters of predictive algorithms. …”
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Machine learning and partial differential equations: benchmark, simplify, and discover by Petros Koumoutsakos

“…Advances in numerical methods, algorithms, software, and hardware over the last 60 years have enabled simulation frontiers that were unimaginable a couple of decades ago. …”
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Enhancing Fraud Detection in Banking With Deep Learning: Graph Neural Networks and Autoencoders for Real-Time Credit Card Fraud Prevention by Fawaz Khaled Alarfaj, Shabnam Shahzadi

“…For real-time fraud detection, we propose Graph neural network with lambda architecture while for credit card fraud detection, we use an autoencoder, validated through case studies from two banks. …”
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AUSPEX: An integrated open-source decision-making framework for UAVs in rescue missions by Björn Döschl, Kai Sommer, Jane Jean Kiam

“…We demonstrate how AUSPEX can be used for generic scenarios in SAR missions while highlighting its potential for future extensibility.…”
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Harnessing Artificial Intelligence in Cardiology: Advancements in Diagnosis, Treatment, and Patient Care by Muhammad Hamza Shuja, Firzah Shakil, Syed Hasan Shuja, Minal Hasan, Maliha Edhi, Abeera Farooq Abbasi, Afia Jawaid, Shajia Shakil

“…Furthermore, AI enhances surgical outcomes through real-time assistance and precision. While AI’s potential in cardiology is vast, ethical considerations and challenges such as data privacy, bias, and the “black box” nature of some algorithms must be addressed. …”
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