Label credibility correction based on cell morphological differences for cervical cells classification by Wenbo Pang, Yue Qiu, Shu Jin, Huiyan Jiang, Yi Ma

“…Noisy labels due to this reason are a great challenge for supervised learning. To address the problem caused by noisy labels, we propose a method based on label credibility correction for cervical cell images classification network. …”
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ENHANCING ENGLISH PRONUNCIATION STRESS PATTERNS THROUGH LYRIC-BASED SONG ON SPOTIFY by Marrieta Moddies Swara, Lutfia Adinda, Imam Sudarmaji

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Modern Opportunities Increasing Motivation of Students to Study by Besh L., Dmytryshyn B., Besh О., Yaskevych О., Matsyura О.

“…Motivational component of learning activities covers cognitive needs, motives and sense of education. …”
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An enhanced framework for knowledge graph embedding based on negative sample analogical reasoning by Huimin Li, Yuhu Tao, Dan Chen, Yi Tang, Jianxiao Wang, Lulu Xue

“…While enhancing KGE models through analogical reasoning offers a potential solution, current approaches typically depend on positive samples that are similar to the target for learning analogy embeddings. …”
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How leader–member exchange affects university teachers’ scholarship of teaching and learning performance: a comprehensive analysis of psychological capital, LMX differentiation, an... by Jiashuai Fang, Jiashuai Fang, Qian Zhang, Peiya Rao, Guanghua Ouyang

“…This study examines how leader-member exchange (LMX) affects university teachers’ SoTL performance, considering psychological capital as a mediator and LMX differentiation and traditionality as moderators.MethodsBased on social exchange theory, resource conservation theory, and social comparison theory, this study developed a cross-level three-order regulatory moderated mediation model. …”
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Benchmarking Accelerometer and CNN-Based Vision Systems for Sleep Posture Classification in Healthcare Applications by Minh Long Hoang, Guido Matrella, Dalila Giannetto, Paolo Craparo, Paolo Ciampolini

“…This research presents a comparative analysis of sleep position recognition using two distinct approaches: image-based deep learning and accelerometer-based classification. …”
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Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, E... by Daniel Niguse Mamo, Tesfahun Melese Yilma, Makda Fekadie Tewelgne, Yakub Sebastian, Tilahun Bizuayehu, Mequannent Sharew Melaku, Agmasie Damtew Walle

“…This study used different machine learning classification algorithms to predict the features that cause virological failure in HIV-positive patients. …”
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The effect of implementation leadership training for nursing informal leaders in the evidence-based practice by Xueyan Huang, Can Wang, Lumeng Lu, Jianao Chen, Rui Wang, Ying Feng, Yuhong Dong, Haifang Zhou

“…BackgroundImplementation leadership is important for the successful implementation of evidence-based practice (EBP). Informal leaders, who are important promoters of EBP in nursing in the current healthcare system, can affect nursing management, organizational effectiveness, and cultural quality positively. …”
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Integrating Street View Images, Deep Learning, and sDNA for Evaluating University Campus Outdoor Public Spaces: A Focus on Restorative Benefits and Accessibility by Tingjin Wu, Deqing Lin, Yi Chen, Jinxiu Wu

“…This study applied the semantic segmentation technique of the deep learning model to extract the feature indicators of outdoor public space based on street view image (SVI) data. …”
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Enhancing the reliability and accuracy of wireless sensor networks using a deep learning and blockchain approach with DV-HOP algorithm for DDoS mitigation and node localization by Bhupinder Kaur, Deepak Prashar, Leo Mrsic, Ahmad Almogren, Ateeq Ur Rehman, Ayman Altameem, Seada Hussen

“…The remedy to these challenges in this work is a solution based on deep learning integrated with a blockchain-aided distance-vector hop (DV-HOP) localization algorithm for reliable and secure node localization. …”
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Deep 3D World Models for Multi-Image Super-Resolution Beyond Optical Flow by Luca Savant Aira, Diego Valsesia, Andrea Bordone Molini, Giulia Fracastoro, Enrico Magli, Andrea Mirabile

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PanoSCU: A Simulation-Based Dataset for Panoramic Indoor Scene Understanding by Mariia Khan, Yue Qiu, Yuren Cong, Jumana Abu-Khalaf, David Suter, Bodo Rosenhahn

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The Use of Concept Maps in the Process of Independent Study of Educational Material in Higher Mathematics by Larisa Norik, Irina Lebedeva

“…Methodology. Based on a review of the main provisions of modern theory of learning and generalization of research results presented in scientific papers on the scope of application of concept maps in the learning process, such a training experiment was conducted. …”
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Artificial intelligence-based model for diagnosing Helicobacter pylori in whole-slide images by Kehan Teng, Lihua Ren, Xiaoyu Yan, Yawei Duan, Zhe Chen, Hansheng Li, Lihua Zhang, Lei Cui

“…We aimed to use artificial intelligence (AI) models to improve the accuracy and efficiency of H. pylori diagnosis and to reduce the workload of pathologists.MethodsHere, we developed three multi-instance learning (MIL) models: AB-MIL, DS-MIL, and Trans-MIL, to automatically detect H. pylori infection. …”
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Instruction and demonstration-based secure service attribute generation mechanism for textual data by LI Chenhao, WANG Na, LIU Aodi

“…Traditionally, the calibration of secure service attribute for textual data has been primarily reliant on human experts and machine learning methods, yet the efficiency and few-shot ability are insufficient. …”
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A novel pedestrian detection algorithm based on data fusion of face images by Jianhu Zheng, Jinshuan Peng

“…Statistical learning theory is a research specialization of machine learning, especially applicable to small samples. …”
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Accuracy of artificial intelligence-based segmentation in maxillofacial structures: a systematic review by Manea Alahmari, Maram Alahmari, Abdulmajeed Almuaddi, Hossam Abdelmagyd, Kumuda Rao, Zaid Hamdoon, Mohammed Alsaegh, Nallan C. S. K. Chaitanya, Shishir Shetty

“…Other metrics, such as sensitivity and precision, were variably reported, with sensitivity exceeding 90% across studies. Conclusion AI-based segmentation, particularly using deep-learning models, demonstrates high accuracy in the segmentation of dental and maxillofacial structures, comparable to expert manual segmentation. …”
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Developing Machine-Learning Models to Predict Bacteremia in Febrile Adults Presenting to the Emergency Department: A Retrospective Cohort Study from a Large Center by Chia-Ming Fu, Ike Ngo, Pak Sheung Lau, Yaroslav Ivanchuk, Fan-Ya Chou, Chih-Hung Wang, Chien-Yu Lin, Chu-Lin Tsai, Shey-Ying Chen, Tsung-Chien Lu, Hung-Yu Wei

“…Conclusion: Our machine-learning model has shown excellent discriminatory performance to predict bacteremia based only on clinical features at ED triage. …”
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Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

“…This study aims to predict 6-month non-remission in 222 disease-modifying anti-rheumatic drug (DMARD)-naïve RA patients initiating methotrexate monotherapy, using baseline patient characteristics from the ARCTIC trial.MethodsMachine learning models were developed utilizing twenty-one baseline demographic, clinical and laboratory features to predict non-remission according to ACR/EULAR Boolean, SDAI and CDAI criteria. …”
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Multibody Nonrigid Structure from Motion Segmentation Based on Sparse Subspace Clustering by Wenqing Huang, Qingfeng Hu, Yaming Wang, Mingfeng Jiang

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