Explainable data mining model for hyperinsulinemia diagnostics by Nevena Rankovic, Dragica Rankovic, Mirjana Ivanovic, Igor Lukic

“…Medical datasets are often highly imbalanced and may contain irrelevant features that hinder predictive performance. To address these challenges in the medical data analysis, we propose a model employing Functional Principal Component Analysis (FPCA), which also accounts for outliers that could otherwise lead to the inclusion of irrelevant features. …”
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Preliminary analysis of acoustic detection of the Red-throated Caracara in northern Costa Rica by Roberto Vargas-Masís, Diego Quesada

“…This study focused on the use of Pattern Matching to detect the presence of the Red-Throated Caracara in northern Costa Rica using a large number of sound recordings and its validation with metrics such as Accuracy, Precision Negative predictive value, Sensitivity, Specificity and Unweighted average recall. …”
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Metro Timetabling for Time-Varying Passenger Demand and Congestion at Stations by Keping Li, Hangfei Huang, Paul Schonfeld

“…Branch-and-bound and frequency determining algorithms are designed to solve OST. A novel rolling optimization algorithm is designed to solve OH. …”
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A Multi-Model Machine Learning Framework for Identifying Raloxifene as a Novel RNA Polymerase Inhibitor from FDA-Approved Drugs by Nhung Thi Hong Van, Minh Tuan Nguyen

“…Using the PubChem dataset AID 588519, our ensemble models achieved the highest performance with accuracy, ROC-AUC, and F1 scores higher than 0.70, while the CNN model demonstrated complementary predictive value with a specificity of 0.77 on external validation. …”
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TSCAPE: time series clustering with curve analysis and projection on an Euclidean space by Jeremy Renaud, Raphaël Couturier, Christophe Guyeux, Benoit Courjal

“…The results demonstrate the method's superiority over “only distance comparison clustering techniques”, like dynamic time warping and K-Means, with future prospects aimed at predictive applications and refining the clustering process by exploring alternative, more powerful clustering algorithms.…”
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The Future of Minimally Invasive GI and Capsule Diagnostics (REFLECT), October 2024 by Lea Østergaard Hansen, Alexandra Agache, Anastasios Koulaouzidis

“…The symposium also highlighted the significance of predictive models for patient selection and developments in panenteric CE. …”
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Innovative data techniques for centrifugal pump optimization with machine learning and AI model. by Gaurav Sandeep Dave, Amar Pradeep Pandhare, Atul Prabhakar Kulkarni, Dhananjay Vasant Khankal

“…Additionally, it decreases model training time by 180 seconds, facilitating predictive maintenance of critical performance metrics and minimizing downtime. …”
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Artificial intelligence-augmented smart grid architecture for cyber intrusion detection and mitigation in electric vehicle charging infrastructure by Ankita Sharma, Shalli Rani, Mohammad Shabaz

“…By leveraging real-time data analytics, the system enables predictive threat mitigation and energy load balancing through vehicle-to-grid (V2G) technologies. …”
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Treatment response rate and life prognosis at autoimmune liver diseases by K. V. Ivashkin, Ye. N. Shirokova, V. T. Ivashkin

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Hybrid modeling of structure extension and instance weighting for naive Bayes by Yu Liangjun, Wang Di, Zhou Xian, Wu Xiaomin

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Sparse transformer and multipath decision tree: a novel approach for efficient brain tumor classification by Pengcheng Li, Yuqi Jin, Monan Wang, Fengjie Liu

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Impact of AI and Machine Learning on Financial Services by Patil Smita, Mailcontractor Rahul

“…Advanced data analytics, automation, and predictive tools powered by AI (Artificial Intelligence) and Machine Learning (ML) are reshaping the global financial services sector, promoting innovation and enhancing efficiency across the sector. …”
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Research on Online Defect Detection Method of Solar Cell Component Based on Lightweight Convolutional Neural Network by Huaiguang Liu, Wancheng Ding, Qianwen Huang, Li Fang

“…Secondly, in order to detect the defects with small size or weak edges in the silicon wafer, an improved lightweight CNN model with deep backbone feature extraction network structure was proposed, as the enhancing feature fusion layer and the three-scale feature prediction layer; the model provided more feature detail. …”
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Method for detecting cracks in retaining walls based on improved YOLOv5s by Yanhai Wang, Chenxin Guo, Guoyong Duan, Yuhao Zhang, Chao Yang, Huafeng Deng

“…The experimental results showed that the improved algorithm reduced the number of YOLOv5s parameters by 12% and increased the average precision by 1.5% compared to YOLOv5s using only the rotating prediction frames. …”
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Automated Text Structuring: Natural Language Processing and Regular Expressions in XML Tag Filling by Ivan P. Malashin, Vadim S. Tynchenko, Andrei P. Gantimurov, Vladimir A. Nelyub, Aleksei S. Borodulin

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Detecting Covid-19 Fake News on Twitter/X in French: Deceptive Writing Strategies by Ming Ming Chiu, Alex Morakhovski, Zhan Wang, Jeong-Nam Kim

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Results of the study of source conditions indicative factors of parodontal status and local immunity of oral cavity besides flying personnel of the civil aviation by G. G. Ashurov, M. K. Shokirov, S. M. Karimov

“…At study of immunological conditions of oral cavity besides flying personnel of IV group revealed reduction of lysosome activity and increasing of immunoglobulin level that is indicative of reduction humeral protection of oral cavity.CONCLUSION. …”
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Identification of lactylation-related biomarkers in osteoporosis from transcriptome and single-cell data by Jiafeng Peng, Hongxing Zhang, Huaize Wang, Ting Jiang, Minglei Gao, Xingfu Ma, Yingzong Xiong, Yingchun Li, Ran Xu, Junchen Zhu

“…The nomogram showed that these two biomarkers could accurately predict OP risk. Functional analysis revealed that CSRP2 and FUBP1 were closely associated with inflammation regulation. …”
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Machine learning‐guided plasticity model in refractory high‐entropy alloys by Shang Zhao, Jinshan Li, Weijie Liao, Ruihao Yuan

“…Through feature selection techniques, a critical subset of features is identified, enabling a support vector classification model to achieve 96% prediction accuracy. Additionally, an interpretable machine learning algorithm is employed to derive explicit functional expressions describing the relationship between key features and fracture strain, achieving 88% accuracy. …”
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AI-Enabled Digital Marketing in Startups: A Systematic Review of Global Practices and Egyptian Implementation Challenges by Wael Bedda, Heba Al-Ashry, Hamed Ead

“…By systematically reviewing 21 studies (2017–2023) from Scopus, Web of Science, and Science Direct, the research highlights how AI enhances engagement with customers, improves campaign results, and boosts prediction abilities. Key findings reveal that AI tools, such as chatbots and predictive analytics, improve personalization, with some studies reporting an increase in conversion rates in emerging markets. …”
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