Review on the Innovation of Investment Banks’ Credit Risk Assessment System in a Highly Volatile Market by Wei Yakun

“…Challenges such as model interpretability and data quality persist, necessitating future research on explainable AI and ESG integration. …”
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A Neutrosophic Logic Ruled Based Machine Learning Approaches for Chronic Kidney Disease Risk Prediction by Bhabani S. Mohanty, Krishna Priya R, Liya Alias, R. Vijaya Kumar Reddy, Prasanta Kumar Raut, Samson Isaac, Manibharathi.D, C. Saravanakumar, Nihar Ranjan Panda, Said Broumi

“…This research suggests a novel machine-learning technique to create a reliable and accurate CKD risk prediction model by combining neutrosophic logic with various classification algorithms. …”
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The vessel movement optimisation with excessive control by С. Зинченко, А. Бень, П. Носов, И. Попович, В. Матейчук, О. Грошева

“…It is concluded that the development of such systems is relevant. Mathematical, algorithmic, and software have been developed for an onboard controller simulator of a vessel’s motion control system with excessive control, the operability and efficiency of which has been verified by numerical simulation in a closed circuit with a mathematical model of the control object for various types of vessels, navigation areas and weather conditions. …”
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Attentional bias for alcohol cues in visual search-Increased engagement, difficulty to disengage or both? by Janika Heitmann, Nienke C Jonker, Brian D Ostafin, Peter J de Jong

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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

“…AI technologies, including predictive modeling and ML algorithms such as random forests and convolutional neural networks (CNNs), can analyze diverse data sources—such as meteorological, environmental, and health records—to detect patterns and predict outbreaks. …”
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Streamlining Thoracic Radiotherapy Quality assurance: One-Class Classification for Automated OAR Contour Assessment by Yihao Zhao BSc, Cuiyun Yuan MSc, Ying Liang PhD, Yang Li MSc, Chunxia Li MSc, Man Zhao MSc, Jun Hu PhD, Ningze Zhong Bsc, Wei Liu PhD, Chenbin Liu PhD

“…Purpose Automating quality assurance (QA) for contours generated by automatic algorithms is critical in radiotherapy treatment planning. …”
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Optimization of transportation efficiency through fuzzy logic and LINGO software by Zahoor Ahmad Ganie, Zahid Gulzar Khaki, Tanveer Ahmad Tarray, Gazala Salam, Eid Sadun Alotaibi

“…Intuitionistic fuzzy programming and randomized response techniques have been adapted in this proposed methodology to overcome data privacy, cost-effectiveness, and minimization of variation within strata problems. The model was confirmed to be able to lower standard errors, maintain data integrity, and improve transportation management in computational tests. …”
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CoMSeC: A Comparative Analysis of Various Service Classification Techniques by Malabika Das, Ansh Sarkar, Sujata Swain

“…This paper aims to formulate a novel classification model and conduct a comparative study to analyze the performance of base models with various classical and modern clustering algorithms. …”
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An Edge Container Migration Optimization Method for Multi-service Intelligent Resource Scheduling of Distribution Networks by Shuai LI, Di XU, Xiangyu WEN, Jiaxin ZHANG

“…The simulation results demonstrate that compared with traditional algorithms, the proposed method can validly improve the data processing delay performance for distribution network.…”
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EDITORIAL: ARTIFICIAL INTELLIGENCE AND ITS TRANSFORMATIVE IMPACT ON SCIENTIFIC PUBLISHING by Abubakar Munir

“…Besides peer review, AI has also improved the editorial process by employing language processing models that assist authors in manuscript editing. …”
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Conformal prediction for uncertainty quantification in dynamic biological systems. by Alberto Portela, Julio R Banga, Marcos Matabuena

“…These approaches can provide non-asymptotic guarantees, improving robustness and scalability across various applications, even when the predictive models are misspecified. …”
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Software Defect Prediction For Quality Evaluation Using Learning Techniques Ensemble Stacking by Muhammad Romadhona Kusuma, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…This research aims to improve the software quality and effectiveness of zakat management by the National Amil Zakat Agency (BAZNAS) through the development of a software defect prediction model (SDPM). …”
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NLP-Based Fusion Approach to Robust Image Captioning by Riccardo Ricci, Farid Melgani, Jose Marcato Junior, Wesley Nunes Goncalves

“…Despite indisputable improvements in performance, we argue that relying on the output of a single model can be critical, especially when data scarcity limits the generalization capability of the trained algorithms. …”
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Temporal Attention-Enhanced Stacking Networks: Revolutionizing Multi-Step Bitcoin Forecasting by Phumudzo Lloyd Seabe, Edson Pindza, Claude Rodrigue Bambe Moutsinga, Maggie Aphane

“…The proposed Temporal Attention-Enhanced Stacking Network (TAESN) integrates the complementary strengths of diverse machine learning algorithms while emphasizing critical temporal features, leading to substantial improvements in forecasting accuracy over traditional methods. …”
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Efficient structure learning of gene regulatory networks with Bayesian active learning by Dániel Sándor, Péter Antal

“…Our results demonstrate that integrating active learning into structure learning algorithms can significantly improve performance, offering a scalable and effective approach for gene regulatory network discovery.…”
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Optimal sleep time controller based on traffic prediction and residual energy in duty-cycled wireless sensor networks by Haibo Luo, Minghua He, Zhiqiang Ruan, Xiaxia Zeng

“…Performance results show that our proposed algorithms can balance power consumption among nodes and improve power efficiency while guaranteeing packet latency is minimized.…”
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Optimized hybrid SVM-RF multi-biometric framework for enhanced authentication using fingerprint, iris, and face recognition by Sonal, Ajit Singh, Chander Kant

“…The integration of support vector machine (SVM) and random forest (RF) classifiers, along with optimization techniques like bacterial foraging optimization (BFO) and genetic algorithms (GA), improves efficiency and robustness. …”
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Predicting 30-Day Venous Thromboembolism Following Total Joint Arthroplasty: Adjusting for Trends in Annual Length of Stay by Johnathan R. Lex, MBChB, MASc, Robert Koucheki, MD, MEng, Aazad Abbas, MD, Jesse I. Wolfstadt, MD, MSc, FRCSC, FAAOS, Alexander S. McLawhorn, MD, MBA, Bheeshma Ravi, MD, PhD, FRCSC

“…Development of more accurate machine learning models for VTE prediction may improve risk stratification, prevention, and monitoring for arthroplasty patients.…”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…A cost-effectiveness study estimated cost per point improvement in the Roland–Morris Disability Questionnaire. …”
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Understanding discrepancies in soil moisture from SMAP and AMSR2: insights into performance and dry-down behavior by Zhiqing Peng, Tianjie Zhao, Jiancheng Shi, Lu Hu, Thomas J. Jackson, Michael H. Cosh, Hui Lu, Xiaodong Gao, Jingyao Zheng, Panpan Yao, Qian Cui, Peng Guo, Peilin Song, Zushuai Wei, Mengjia Wang, Anmin Fu

“…These results highlight the importance of considering differences in payload configurations when using remote sensing SM products for studies of land–atmosphere interactions in hydrometeorology and for improving land surface models (LSMs).…”
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