SCREENING FOR OVARIAN CANCER: REALITY AND PROSPECTS. REVIEW OF THE LITERATURE by E. V. Gerfanova, L. A. Ashrafyan, I. B. Antonova, O. I. Aleshikova, S. V. Ivashina

“…Currently, none of the presented algorithms can meet the criteria of economic efficiency, even in the most developed countries. …”
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Perceived worries in the adoption of artificial intelligence among nurses in neonatal intensive care units by Ahmad Ayed, Ahmad Batran, Ibrahim Aqtam, Malakeh Z. Malak, Moath Abu Ejheisheh, Mosaab Farajallah, Lamees Farraj, Sanaa Alkhatib

“…Abstract Introduction Artificial Intelligence (AI) comprises computational algorithms designed to analyze data, learn patterns, and execute tasks traditionally requiring human cognition. …”
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Estimation of Reference Crop Evapotranspiration in the Yellow River Basin Based on Machine Learning and Its Regional and Drought Adaptability Analysis by Jun Zhao, Huayu Zhong, Congfeng Wang

“…These models represent a range of algorithmic structures, from nonlinear ensemble methods (RF, GB) to kernel-based regression (SVR) and linear regularized regression (Ridge). …”
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How Do Ethical Factors Affect User Trust and Adoption Intentions of AI-Generated Content Tools? Evidence from a Risk-Trust Perspective by Tao Yu, Yihuan Tian, Yihui Chen, Yang Huang, Younghwan Pan, Wansok Jang

“…Through a systematic literature review and expert interviews, eight core ethical dimensions were identified: Misinformation (MIS), Accountability (ACC), Algorithmic Bias (ALB), Creativity Ethics (CRE), Privacy (PRI), Job Displacement (JOD), Ethical Transparency (ETR), and Control over AI (CON). …”
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Peculiarities of dynamic evaluation of globular formation outlines of the lungs with multislice computed tomography by Vladimir G. Kolmogorov, Ivan V. Molodkin, Vladimir K. Konovalov, Alexander M. Shayduk, Sergey A. Ostanin, Sergey L. Leonov, Olga V. Borisenko, Mikhail A. Fedoseyev, Julia S. Modakalova

“…To develop a methodology for assessing the GFL outlines of the dynamics of multislice computed tomography (MSCT) by selecting the optimal image processing algorithms.Materials and methods. The visual analysis of two- component physical model images of the electronic window level (WL) and electronic window width (WW) was installed on the basis of the best conditions for studying a specific group of tissues. …”
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Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study by Mengdie Liu, Wen Guo, Jin Peng, Jinhui Wu

“…Feature selection was performed using Lasso Regression, XGBoost, and Random Forest machine learning algorithms, and a nomogram model was developed using univariate and multivariate Cox regression analyses, with validation of its accuracy, concordance, and clinical applicability.ResultsA total of 12 feature variables were identified through the combined use of three machine learning methods. …”
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Artificial intelligence applied to the study of human milk and breastfeeding: a scoping review by Sergio Agudelo-Pérez, Daniel Botero-Rosas, Laura Rodríguez-Alvarado, Julián Espitia-Angel, Lina Raigoso-Díaz

“…Prediction of exclusive breastfeeding patterns: AI models, such as decision trees and machine learning algorithms, identify factors influencing breastfeeding practices, including maternal experience, hospital policies, and social determinants, highlighting actionable predictors for intervention. 2. …”
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Datafikasi Fandom K-Pop: Transformasi Identitas Pribadi dan Sosial di Era Digital by Ersa Putri Nabila, Innayah Pitopili, Muhammad Fakhri Rahmadi, Muhammad Haydar

“…Through in-depth interviews with 12 K-Pop fans who have been involved in idol voting activities, the study investigates how social media and algorithms are perceived to influence fan experiences, foster a sense of community solidarity, and contribute to reinterpreting their identities in digital spaces. …”
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Fine-Tuning Retrieval-Augmented Generation with an Auto-Regressive Language Model for Sentiment Analysis in Financial Reviews by Miehleketo Mathebula, Abiodun Modupe, Vukosi Marivate

“…Supervised learning algorithms have been popularly employed for this task, but the performance of these models has been compromised due to the brevity of the content and the presence of idiomatic expressions, sound imitations, and abbreviations. …”
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Identifying key palmitoylation-associated genes in endometriosis through genomic data analysis by Jinyan Kai, Jiaqi Su, Yinping You, Xiaoliang Liang, Haitao Huang, Jie Fang, Qiong Chen

“…The intersection of these key modular genes with DEGs yielded a refined gene set. Machine learning algorithms were then applied to further optimize gene selection, followed by external validation, immune infiltration analysis, RNA network construction, and exploration of potential targeted drug candidates. …”
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Artificial Intelligence for Multiclass Rhythm Analysis for Out-of-Hospital Cardiac Arrest During Mechanical Cardiopulmonary Resuscitation by Iraia Isasi, Xabier Jaureguibeitia, Erik Alonso, Andoni Elola, Elisabete Aramendi, Lars Wik

“…A total of 15,479 segments (2406 Sh, 5481 AS, and 7592 OR) were extracted from 2058 patients during LDB CCs, whereof 9666 were used to train the algorithms and 5813 to assess the performance. The proposed architecture consists of an adaptive filter for CC artifact suppression and a multiclass rhythm classifier. …”
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Simultaneous multi-class detection of interplanetary space weather events by Nguyen Gautier, Bernoux Guillerme, Ferlin Antoine

“…Our approach is inspired by the You Only Look Once (YOLO) family of algorithms, widely used in object detection. It works by directly identifying candidate time intervals, providing quick visual indicators of event occurrences that can be readily used by human observers in an operational space weather context. …”
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Enhancing stroke prediction models: A mixing of data augmentation and transfer learning for small-scale dataset in machine learning by Imam Tahyudin, Ade Nurhopipah, Ades Tikaningsih, Puji Lestari, Yaya Suryana, Edi Winarko, Eko Winarto, Nazwan Haza, Hidetaka Nambo

“…The classification models employed in this study were four algorithms: Random Forest, Support Vector Machine, Gradient Boosting, and Extreme Gradient Boosting. …”
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A New Approach to Characterize Superplastic Materials from Free-Forming Test and Inverse Analysis by Gillo Giuliano, Wilma Polini

“…It allows for a reduction in the number of constants needed to determine the material constitutive equation, thus requiring low simulation time compared to models that adopt the multiple-objective optimization based on genetic algorithms (GAs). It is more suitable to be used in the industrial field. …”
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Deciphering the role of miR-71 in Echinococcus multilocularis early development in vitro. by Matías Gastón Pérez, Markus Spiliotis, Natalia Rego, Natalia Macchiaroli, Laura Kamenetzky, Nancy Holroyd, Marcela Alejandra Cucher, Klaus Brehm, Mara Cecilia Rosenzvit

“…Using genomic information and bioinformatic algorithms for miRNA binding prediction, we found a high number of potential miR-71 targets in E. multilocularis. …”
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A High Resolution Melting Analysis (HRM) PCR assay for the detection and identification of Old World Leishmania species. by Yusr Saadi-Ben Aoun, Hejer Souguir, Hamed Chouaieb, Mongia Kraiem, Insaf Bel Hadj Ali, Ahmed S Chakroun, Florian Noguier, Akila Fathallah-Mili, David Piquemal, Ikram Guizani

“…Its integration into molecular diagnostic algorithms for CL or in eco-epidemiological studies holds promise for improving disease management and control.…”
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Improving the Performance of Electrotactile Brain–Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials by Marija Novičić, Olivera Djordjević, Vera Miler-Jerković, Ljubica Konstantinović, Andrej M. Savić

“…We systematically tested classification performance using machine learning algorithms, including logistic regression, k-nearest neighbors, support vector machines, random forests, and artificial neural networks. …”
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A Soft Sensor Based Inference Engine for Water Quality Assessment and Prediction by Micheal A Ogundero, Theophilus A Fashanu, Foluso O Agunbiade, Kehinde Orolu, Ahmed A Yinusa, Usman A Daudu, Muhammed O H Amuda

“…Results show that machine learning algorithms including the Logistic Regression, Decision Trees, Random Forest, XGBoost, and Neural Networks schemes reliably predicted water potability in the absence of two missing instrumentation parameters namely: pH and DO. …”
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Distribution of University Admission Quotas: Problems of Competitive Selection Process by L. M. Nurieva, S. G. Kiselev

“…The main reason for the inability of the competitive mechanism to carry out the correct ranking of participants in terms of success is the major methodological and mathematical errors inherent in the algorithms for determining the effectiveness of educational organisations. …”
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Machine learning-based prediction model for brain metastasis in patients with extensive-stage small cell lung cancer by Erha Munai, Siwei Zeng, Ze Yuan, Dingyi Yang, Yong Jiang, Qiang Wang, Yongzhong Wu, Yunyun Zhang, Dan Tao

“…Four different machine learning (ML) algorithms were used to create prediction models for BMs in ES-SCLC patients. …”
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