Automatic Subject Cataloguing at the German National Library by Christoph Poley, Sandro Uhlmann, Frank Busse, Jan-Helge Jacobs, Maximilian Kähler, Matthias Nagelschmidt, Markus Schumacher

“…Today, the DNB uses open source algorithms and frameworks to assign various types of thematic meta information in this way. …”
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Genetically distinct within-host subpopulations of hepatitis C virus persist after Direct-Acting Antiviral treatment failure. by Lele Zhao, Matthew Hall, Prahalad Giridhar, Mahan Ghafari, Steven Kemp, Haiting Chai, Paul Klenerman, Eleanor Barnes, M Azim Ansari, Katrina Lythgoe

“…Given the short-read nature of the data, we used a number of methods to identify distinct within-host lineages including tracking concordance in intra-host nucleotide variant (iSNV) frequencies, applying sequenced-based and tree-based clustering algorithms to sliding windows along the genome, and haplotype reconstruction. …”
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Adaptive gradient scaling: integrating Adam and landscape modification for protein structure prediction by Vitalii Kapitan, Michael Choi

“…Despite their success, machine learning methods face fundamental limitations in optimizing complex high-dimensional energy landscapes, which motivates research into new methods to improve the robustness and performance of optimization algorithms. Results This study presents a novel approach to protein structure prediction by integrating the Landscape Modification (LM) method with the Adam optimizer for OpenFold. …”
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Development and evaluation of deep neural networks for the classification of subtypes of renal cell carcinoma from kidney histopathology images by Amit Kumar Chanchal, Shyam Lal, Shilpa Suresh

“…Recently, deep learning algorithms have gained significant attention in histopathology image analysis. …”
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Landslide Hazard Assessment Under Record-Breaking Extreme Rainfall: Integration of SBAS-InSAR and Machine Learning Models by Wenbo Zheng, Wen Fan, Yanbo Cao, Yalin Nan, Pengxu Jing

“…The proposed framework integrates cumulative extreme rainfall metrics with subtle ground deformation indicators and applies four advanced machine learning algorithms—DNN, XGBoost, RF, and LightGBM—for multidimensional hazard assessment. …”
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Ethical and social considerations of applying artificial intelligence in healthcare—a two-pronged scoping review by Emanuele Ratti, Michael Morrison, Ivett Jakab

“…However, in the rapidly developing field of AI, developments such as machine learning, neural networks, generative AI, and large language models have the potential to raise new and distinct ethical and social issues compared to, for example, automated data processing or more ‘basic’ algorithms. Methods This article presents a scoping review of the ethical and social issues pertaining to AI in healthcare, with a novel two-pronged design. …”
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Development and validation of a machine-learning model for the risk of potentially inappropriate medications in elderly stroke patients by Xiaodan Yang, Qianqian Ye, Mengxiang Zhang, Yuewei Xu, Manqin Yang

“…ObjectiveTo construct a risk prediction model for potentially inappropriate medications (PIM) in elderly stroke patients based on multiple machine-learning algorithms, providing decision support to identify high-risk patients and ensure rational clinical medication use.MethodsA total of 1,252 discharged stroke patients from a tertiary hospital in Anhui Province, China, were included from January 2023 to December 2024. …”
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A Workflow for Integrated Geological Modeling for Shale Gas Reservoirs: A Case Study of the Fuling Shale Gas Reservoir in the Sichuan Basin, China by Xiaofei Shang, Huawei Zhao, Shengxiang Long, Taizhong Duan

“…The selection and optimization of modeling methods, the innovation and development of modeling algorithms, and the evaluation techniques for model uncertainty are areas where breakthroughs may be possible in the geological modeling of shale gas reservoirs. …”
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Identification of M2 macrophage-related genes associated with diffuse large B-cell lymphoma via bioinformatics and machine learning approaches by Jiayi Zhang, Zhixiang Jia, Jiahui Zhang, Xiaohui Mu, Limei Ai

“…Using the Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine Recursive Feature Elimination (SVM-RFE), and Random Forest (RF) algorithms, we screened for seven potential diagnostic biomarkers with strong diagnostic capabilities: SMAD3, IL7R, IL18, FAS, CD5, CCR7, and CSF1R. …”
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Trade-Space Exploration With Data Preprocessing and Machine Learning for Satellite Anomalies Reliability Classification by Abdul Mutholib, Nadirah Abdul Rahim, Teddy Surya Gunawan, Mira Kartiwi

“…Leveraging a Seradata dataset spanning 66 years and 4,455 satellite records, the framework systematically evaluates four data cleaning methods, four data transformation techniques, five normalization strategies, and seven machine learning algorithms across 480 configurations. The optimal configuration, comprising Iterative Imputation, FastText, Robust Scaling, and Decision Tree, achieved the highest testing accuracy of 95.74% with competitive computational efficiency. …”
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A discussion of S.M. Krylov’s book «Neocybernetics» (2008) by E. S. Gornev, I. V. Matyushkin

“…Despite the abstractness of the algebraic-algorithmic approach, Krylov offers a number of specific constructions that are in demand during the fourth industrial revolution and for the future development of industrial technology in nanoelectronics and biotechnology. …”
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Flexible Interconnection Device Planning of Low-Voltage Distribution Station Areas Based on Improved Supply Capability Indicators by ZHANG Rui, LIU Hengchao, ZHANG Guoju, GE Xuefeng, YU Miao

“…Next，a flexible interconnection device planning framework considering the improvement of supply capability，economy，and load transfer constraints under distribution network reconfiguration is established and solved based on the non-dominated sorting genetic algorithms-II. [Results] The results of the case study of the IEEE 14 bus system with contact switches show that the planning model based on the proposed indicators can effectively improve the supply capability of the distribution network under actual load distribution. …”
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Radiofrequency Technologies of Local Positioning in Healthcare by D. S. Bragin, I. V. Pospelova, I. V. Cherepanova, V. N. Serebryakova

“…Given this, it is necessary to use complex algorithms to detect an object with accuracy to a specific room. …”
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Evaluation of the effectiveness of communications between the Department of transport and Development of road transport infrastructure of Moscow and the population within the frame... by R. A. Abramov, Yu. Yu. Temnikova

“…The approaches and analysis algorithms proposed in the article are applicable for media audit and optimisation of information activities of authorities of different levels.…”
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Research Progress and Applications of Artificial Intelligence in Agricultural Equipment by Yong Zhu, Shida Zhang, Shengnan Tang, Qiang Gao

“…Nevertheless, intelligent agricultural equipment still faces technical challenges regarding data sample acquisition, adaptation to complex field environments, and the coordination between algorithms and hardware. Looking ahead, the convergence of digital twin (DT) technology, edge computing, and big data-driven collaborative optimization is expected to become the core of next-generation intelligent agricultural systems. …”
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Using Machine Learning and Nationwide Population-Based Data to Unravel Predictors of Treated Depression in Farmers by Pascal Petit, Vincent Bonneterre, Nicolas Vuillerme

“…To complement these traditional studies, big data and machine learning (ML) can advantageously be harnessed. While ML algorithms have shown high accuracy in identifying depression predictors in mental health research, no study has yet applied ML in farmers. …”
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A comparative ensemble approach to bedload prediction using metaheuristic machine learning by Ajaz Ahmad Mir, Mahesh Patel, Fahad Albalawi, Mohit Bajaj, Milkias Berhanu Tuka

“…Thus, it can be concluded from the current study that the utilization of ML algorithms can improve accuracy, providing valuable insights for hydraulic engineers and highlighting the importance of ML models in civil engineering practices, particularly in bedload transport prediction.…”
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Structural and population-based evaluations of TBC1D1 p.Arg125Trp. by Tom G Richardson, Elaine C Thomas, Richard B Sessions, Debbie A Lawlor, Jeremy M Tavaré, Ian N M Day

“…Structural prediction involved the use of three separate algorithms; Robetta, HHpred/MODELLER and I-TASSER. We used the transmission disequilibrium test (TDT) to investigate familial association in the ALSPAC study cohort (N = 2,292 mother-offspring pairs). …”
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The Transformative Influence of Artificial Intelligence on Supply Chain Management by Tarihal Balakrishna, Kaliwal Rohit, Ammanagi Ashok

“…This paper aims to explore the effects of AI on supply chains with a particular emphasis on how machine learning and other forms of intelligent algorithms can improve decision-making, operational effectiveness and real-time responsiveness. …”
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Parkinson’s disease detection using inceptionV3: A Deep learning approach by Pallavi M. Shanthappa, Madhwesh Bayari, G.B. Abhilash, K.V. Gokul, P.J. Ashish

“…This study uses deep learning algorithms to classify spiral images traced by patients as an inexpensive diagnostic technique for the detection of PD. …”
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