Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

“…(Research purpose) The aim of this study is to analyze data structures and compare machine learning and deep learning algorithms used in used in crop yield prediction. (Materials and methods) Using a convergent approach and applying methods of cognitive and semantic analysis, the authors examined the subject area of artificial intelligence applications in crop yield prediction. …”
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Redefining customer connections in the UAE’s digital era: A study on emerging technological synergies by Hussam Ali, Ehab Haikal

“…Ethical concerns, including data privacy and algorithmic bias, received a mean score of 3.75, while sustainability challenges, such as e-waste and energy consumption, scored the lowest (mean = 3.20, SD = 0.85). …”
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Construction of machine learning-based prognostic model of centrosome amplification-related genes for esophageal squamous cell carcinoma by LI Chaoqun, ZHENG Hongliang, HUANG Ping

“…A prognostic model of CARGs was constructed by incorporating 12 machine learning algorithms, and univariate and multivariate Cox regression analyses were applied to evaluate whether the 12 models as an independent prognostic factor or not. …”
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AI-Driven Innovation in Skin Kinetics for Transdermal Drug Delivery: Overcoming Barriers and Enhancing Precision by Nubul Albayati, Sesha Rajeswari Talluri, Nirali Dholaria, Bozena Michniak-Kohn

“…Machine learning models trained on extensive molecular datasets predict skin permeability and accelerate the selection of suitable drug candidates. AI-driven algorithms optimize formulations, including penetration enhancers and advanced delivery technologies like microneedles and liposomes, while ensuring safety and efficacy. …”
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Proactive Data Placement in Heterogeneous Storage Systems via Predictive Multi-Objective Reinforcement Learning by Suchuan Xing, Yihan Wang

“…Through comprehensive evaluation using both synthetic and real-world traces from deep learning training workloads, our method demonstrates substantial improvements over state-of-the-art algorithms: achieving up to 45.1% reduction in average I/O latency, 32.5% improvement in throughput for critical applications, and 28.8% reduction in storage costs. …”
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Distinction between concepts of “structural-functional-parametric model” and “parametric model” of information knowledge objects by E. N. Kolybenko

“…To solve practical problems in the subject knowledge area according to the technology of information logical modeling, certain methods, tools, algorithms, and operations are used. The most complete mapping and transformation of information objects is possible only in structural-functional-parametric models and databases of their solutions. …”
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Efficient base metal exploration in northern New Brunswick, Canada through a hybrid ANN integrated with ABC and PSO methods by Claire Dusabemariya, Wei Qian, Romuald Bagaragaza, Ajibola Richard Faruwa, Ali Mossad

“…By integrating Artificial Neural Networks (ANN) with metaheuristic algorithms, specifically Artificial Bee Colony (ABC) and Particle Swarm Optimization (PSO), the research optimizes resistivity inversion techniques to enhance geophysical exploration. …”
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The negative linear relationship between oxidative balance scores and constipation: a cross-sectional study from NHANES 2005–2010 by Liqian Xuan, Yang Chen, Chang Liu, Yahui Dai

“…The three machine learning algorithms including Xgboost, Randomforest, and AdaBoost was used to analyze the important component of OBS in constipation.ResultsA total of 8,074 participants were involved. …”
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E-MONEY FROM THE TECHNOLOGICAL POINT OF VIEW by N. N. Kolosovskaya

“…The analysis of the legal regime of crypto currency circulation allows concluding that this type of electronic algorithms has been developed in order to create an unofficial payment system that does not have a single coordinating center but rather controlled by all users regardless of their location, and, therefore, cannot be “blocked”. …”
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Predicting plant uptake of potential contaminants of emerging concerns using machine learning models (2018–2025): A global review by Alexis Munyengabe, Maria Fezile Banda, Wilma Augustyn

“…The review analyzes diverse ML algorithms, including ensemble models (random forest, gradient boosted regression trees, eXtreme gradient boosting) and deep learning (deep neural networks, recurrent neural networks, long short-term memory) alongside key predictors like soil pH, organic matter, and plant traits. …”
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Geographical Peer Matching for P2P Energy Sharing by Romaric Duvignau, Vincenzo Gulisano, Marina Papatriantafilou, Ralf Klasing

“…Our experimental study, based on real-world energy data, demonstrates that our proposed solutions are efficient both in terms of cost savings achieved by the peers and in terms of communication and computing requirements. Our scalable algorithms thus provide one core building block for practical and data-efficient peer-to-peer energy sharing communities within large-scale optimization systems.…”
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GDDKIA xml service, road traffic incidents data: availability and quality research by Natalia Dziuba, Stanisław Szombara

“…To improve accuracy, additional algorithms were applied that automatically corrected the position of the points to match the nearest roads. …”
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Non-Invasive Continuous Respiratory Monitoring on General Hospital Wards: A Systematic Review. by Kim van Loon, Bas van Zaane, Els J Bosch, Cor J Kalkman, Linda M Peelen

“…Future research in this area should focus on technology explicitly suitable for low care settings and tailored alarm and treatment algorithms.…”
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Enhancing dosimetric precision in the treatment of cancerous tumors: Gamma Index validation and Monte Carlo simulations of 6 and 12 megavoltage photon beams from Varian Medical lin... by Ali H. D. Alshehri

“…The comparative analysis between GAMOS and GATE showed consistent performance, with minor deviations attributable to differences in the underlying simulation algorithms. Furthermore, the study revealed significant insights into the impact of varying field sizes on dose distribution accuracy. …”
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Development of PYMUS+ Code for Quantitative Evaluation of Nuclear Material Accounting (NMA) System by Byung Hee Won, Hee-Sung Shin, Se Hwan Park, Seong-Kyu Ahn

“…For these purposes, in the present study, the PYroprocessing Material flow and MUF Uncertainty Simulation+ (PYMUS+) code, which uses evaluation algorithms to calculate many safeguards factors such as MUF uncertainty, detection probability, and others, was developed. …”
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Trіazolo[1,5-c]quіnazolіnes Synthesis, antimicrobial and antifungal activity [quinazolin-4(3H)-ylidene]hydrazides of carboxylic acids (Message 1) by K. P. Schabelnyk, S.V. Kholodnyak, G.G. Berest, S. І. Kоvalenko, N. M. Polishchuk, O. M. Kamyshnyі

“…The modern standards and algorithms of antimicrobial therapy, that ensure a high level of the treatment’s quality and prevention of the most infectious-inflammatory diseases, provide wide using of chemotherapeutic agents. …”
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Construction of a novel CD8T cell-related index for predicting clinical outcomes and immune landscape in ovarian cancer by combined single-cell and RNA-sequencing analysis by Yu Zhang, Peng Wan, Liangliang Wang, Ruiping Ren

“…Furthermore, immune landscape analysis was performed using CIBERSORT, ssGSEA, TIMER, and ESTIMATE algorithms. Tumor mutation burden (TMB) analysis and drug sensitivity analysis were used to evaluate the potential predictive value of CCAI. …”
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Diagnostic value of the appendicitis inflammatory response (AIR) score. A systematic review and meta-analysis by Roland E. Andersson, Joachim Stark

“…Abstract Background Clinical scoring algorithms are cost efficient in patients with suspicion of acute appendicitis. …”
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Knowledge management system as a basis for smart learning by Natalia V. Dneprovskaya

“…Research in the field of knowledge management remain relevant because, the more perfect the technologies become, that notice the algorithmized work of specialists, the higher the value of creativity for society and the economy.Materials and methods of research include discourse analysis of domestic and foreign scientific sources devoted to the issues of smart education and knowledge management, the systematization of the material. …”
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Translational analysis of data science and causal learning in real-world clinical evaluation of traditional Chinese medicine by Wei Yang, Danhui Yi, XiaoHua Zhou, Yuanming Leng

“…The methodology involves several key steps, including data integration and warehouse building, high-dimensional feature selection, the use of interpretable statistical machine learning algorithms, complex networks, and graph network analysis, knowledge mining techniques such as natural language processing and machine learning, observational study design, and the application of artificial intelligence tools to build an intelligent engine for translational analysis. …”
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