Reassortment Dynamics: Phylogeography and Evolution of H4N9 Influenza Viruses by Nataliia A. Bobrova, Ekaterina D. Lisenenkova, Ekaterina S. Avsievich, Olga N. Mityaeva, Pavel Yu Volchkov, Andrey A. Deviatkin

Get full text

Artificial Intelligence Models and Tools for the Assessment of Drug–Herb Interactions by Marios Spanakis, Eleftheria Tzamali, Georgios Tzedakis, Chryssalenia Koumpouzi, Matthew Pediaditis, Aristides Tsatsakis, Vangelis Sakkalis

“…Artificial intelligence (AI) has emerged as a powerful tool in medical sciences that is revolutionizing various fields of drug research. AI algorithms can analyze large-scale biological data and identify molecular targets and pathways advancing pharmacological knowledge. …”
Get full text

Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…In this paper, we aim to form robust data-driven intelligent algorithms founded on various machine learning methods of Support Vector Machine, Random Forest, AdaBoost, Decision Tree, K-nearest Neighbors, Multilayer Perceptron Artificial Neural Network and Convolutional Neural Network to model solubility of hydrogen/methane blend in brine under realistic conditions of underground hydrogen storage projects by utilizing an experimental dataset collected from the existing body of published research. …”
Get full text

Heterogeneity in willingness to share personal health information: a nationwide cluster analysis of 20,000 adults in Japan by Miho Sassa, Akifumi Eguchi, Keiko Maruyama-Sakurai, Takanori Fujita, Yumi Kawamura, Takayuki Kawashima, Yuta Tanoue, Daisuke Yoneoka, Hiroaki Miyata, Takanori Yamashita, Naoki Nakashima, Shuhei Nomura

“…Clustering analysis using Uniform Manifold Approximation and Projection (UMAP) and Ordering Points to Identify the Clustering Structure (OPTICS) algorithms was performed to identify distinct patterns in sharing preferences. …”
Get full text

A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…The framework holds promise for broader applications in immunoinformatics and autoimmune disease research.…”
Get full text

PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…This study implements multivariate time series forecasting using gradient boosting algorithms (XGBoost, CatBoost, and LightGBM) to predict cash flow patterns in banking transactions, focusing on constructing reliable prediction intervals. …”
Get full text

Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…Abstract Background In the hyper-arid environment of the United Arab Emirates (UAE), understanding rainfall patterns is essential for effective water resource management, agricultural planning, and ecological conservation. …”
Get full text

iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…IMESc permits the customization of plots and saving the workflows into “savepoints” guarantying reproducibility. iMESc bridges the gap between the complexity of machine learning algorithms and the need for user-friendly interfaces in environmental research. …”
Get full text

Artificial Intelligence in cancer epigenomics: a review on advances in pan-cancer detection and precision medicine by Karishma Sahoo, Prakash Lingasamy, Masuma Khatun, Sajitha Lulu Sudhakaran, Andres Salumets, Vino Sundararajan, Vijayachitra Modhukur

“…Aberrant methylation patterns enable early cancer detection and therapeutic stratification; however, their complex patterns necessitates advanced analytical tools. …”
Get full text

Copy-Move Forgery Verification in Images Using Local Feature Extractors and Optimized Classifiers by S. B. G. Tilak Babu, Ch Srinivasa Rao

“…The paper aims to present copy-move forgery detection algorithms with the help of advanced feature descriptors, such as local ternary pattern, local phase quantization, local Gabor binary pattern histogram sequence, Weber local descriptor, and local monotonic pattern, and classifiers such as optimized support vector machine and optimized NBC. …”
Get full text

Progress and trends on machine learning in proteomics during 1997-2024: a bibliometric analysis by Chao Tan, Hao Liu, Zhen Zhang, Xinyu Liu, Yinquan Ai, Xiumin Wu, Enlin Jian, Yongyan Song, Jin Yang

“…Thematic clustering revealed key research foci, including deep learning algorithms, protein–protein interaction prediction, and integrative multi-omics analysis. …”
Get full text

Integrative analysis of RNA-Seq data and machine learning approaches to identify Biomarkers for Rhizoctonia solani resistance in sugar beet by Bahman Panahi, Mahdi Hassani, Nahid Hosseinzaeh Gharajeh

Get full text

Production monitoring and machine tracking in underground mines based on a collision avoidance system: A case study by Artur Skoczylas, Natalia Duda-Mróz, Wioletta Koperska, Paweł Stefaniak, Paweł Śliwiński

Get full text

Dimensionality Reduction problem: a Comprehensive Exploration of Disjoint Principal Component Analysis (DPCA) and Disjoint Multiple Correspondence Analysis (DMCA) by Mario Fordellone

“…We navigate through the intricacies of their algorithms and explore how they unveil patterns within complex datasets. …”
Get full text

MLRec: A Machine Learning-Based Recommendation System for High School Students Context of Bangladesh by Momotaz Begum, Mehedi Hasan Shuvo, Jia Uddin

“…In recent years, many researchers have introduced several models, including neural networks (NNs), machine learning (ML), and deep learning (DL), to identify the impact on student academic performance using a socimedevice. …”
Get full text

«Obscenities give rise to thugs»: Obscene vocabulary in the practice of the poet Vsevolod Nekrasov (based on archive materials) by E. N. Penskaya

“…Without claiming to generalize, this material is focused on identifying patterns and searching for possible algorithms for classifying such phenomena. …”
Get full text

Public Perceptions of Ethical Challenges and Opportunities for Enterprises in the Digital Age by Ahmad Mansour, Khaled Alshaketheep, Hind Al-Ahmed, Ahmad Shajrawi, Arafat Deeb

“…The quantitative analysis methods used in this study encompassed descriptive statistical analysis, inferential statistical analysis, correlation analysis, hypothesis testing, and regression analysis to establish patterns of relationships.  Results: The leading ethical issues for participants were: personal data protection (mean score = 4.2), ethical usage of AI algorithms (mean score = 3.9), job displacement due to AI technology (mean score = 3.1), and the digital divide. …”
Get full text

Optimizing solar maximum power point tracking with adaptive PSO: A comparative analysis of inertia weight and acceleration coefficient strategies by Denesh Sooriamoorthy, Aaruththiran Manoharan, Siva Kumar Sivanesan, Soon Kian Lun, Alexander Chee Hon Cheong, Sathish Kumar Selva Perumal

“…The individual and combined performance of adaptive w, c1 and c2 are evaluated, especially with small and narrow w operational range studied as it contributes to high convergence, especially under fast-changing shading patterns. The results demonstrate that linear adaptive w combined with trigonometric adaptive c1 and c2 consistently achieves high tracking accuracy (99.4%) with minimal steady-state oscillations and faster convergence times (average 0.0642 s), outperforming conventional PSO and P&O algorithms. …”
Get full text

A new method for determining factors Influencing productivity of deep coalbed methane vertical cluster wells by HUANG Li, XIONG Xianyue, WANG Feng, SUN Xiongwei, ZHANG Yixin, ZHAO Longmei, SHI Shi, ZHANG Wen, ZHAO Haoyang, JI Liang, DENG Lin

Get full text

Leveraging environmental microbial indicators in wastewater for data-driven disease diagnostics by Gayatri Gogoi, Gayatri Gogoi, Sarangthem Dinamani Singh, Sarangthem Dinamani Singh, Devpratim Koch, Devpratim Koch, Emon Kalyan, Rashmi Rani Boro, Aradhana Devi, Hridoy Jyoti Mahanta, Hridoy Jyoti Mahanta, Pankaj Bharali, Pankaj Bharali

“…Unsupervised learning algorithms, including K-means and K-medoid clustering, were employed to categorize the data into four distinct clusters, revealing patterns of viral positivity and environmental conditions.ResultsCluster analysis indicated that seasonal variations and water quality characteristics significantly influenced SARS-CoV-2 positivity rates. …”
Get full text