Deep learning-based lung cancer classification of CT images by Mohammad Khalid Faizi, Yan Qiang, Yangyang Wei, Ying Qiao, Juanjuan Zhao, Rukhma Aftab, Zia Urrehman

“…Traditional radiological methods often struggle with high false-positive rates, underscoring the need for advanced diagnostic tools. …”
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Diagnosis of osteosarcoma based on multimodal microscopic imaging and deep learning by Zihan Wang, Jinjin Wu, Chenbei Li, Bing Wang, Qingxia Wu, Lan Li, Huijie Wang, Chao Tu, Jianhua Yin

“…First, the multimodal microscopic images of normal and osteosarcoma tissue slices were collected to characterize the overall morphology of the tissue microenvironment of the samples, the arrangement structure of collagen fibers and the content and distribution of endogenous fluorescent substances. Second, based on the correlation and complementarity of the feature information contained in the three single-mode images, combined with convolutional neural network (CNN) and image fusion methods, a multimodal intelligent diagnosis model was constructed to effectively improve the information utilization and diagnosis accuracy. …”
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Deep Learning-Based Identification of Echocardiographic Abnormalities From Electrocardiograms by Goro Fujiki, MD, Satoshi Kodera, MD, PhD, Naoto Setoguchi, MD, Kengo Tanabe, MD, PhD, Kotaro Miyaji, MD, PhD, Shunichi Kushida, MD, PhD, Mike Saji, MD, PhD, Mamoru Nanasato, MD, PhD, Hisataka Maki, MD, PhD, Hideo Fujita, MD, PhD, Nahoko Kato, MD, PhD, Hiroyuki Watanabe, MD, PhD, Minami Suzuki, MD, Masao Takahashi, MD, PhD, Naoko Sawada, MD, PhD, Jiro Ando, MD, Masataka Sato, MD, Shinnosuke Sawano, MD, PhD, Susumu Katsushika, MD, PhD, Hiroki Shinohara, MD, PhD, Norifumi Takeda, MD, PhD, Katsuhito Fujiu, MD, PhD, Hiroshi Akazawa, MD, PhD, Hiroyuki Morita, MD, PhD, Issei Komuro, MD, PhD

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Strategies for Activating Independent Learning Activities of Students in Biology Classes by Tetiana Mykytyn, Nataliia Dmytrus, Nadiia Kapets, Victoria Gniezdilova

“…Among the innovative methods there are: problem-based learning, projects and research, group work, utilization of internet resources and multimedia, task solving, and independent preparation of presentations or reports. …”
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Dynamic Risk Thresholds for SIEM Alerting Based on Machine Learning by Artur Kapera, Marcin Niemiec

“…In the article, a theoretical concept of a Dynamic Risk-Based Alerting model for SIEM based on machine learning has been presented. …”
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Deep Learning Based Visual Servo for Autonomous Aircraft Refueling by Natthaphop Phatthamolrat, Teerawat Tongloy, Siridech Boonsang, Santhad Chuwongin

“…The proposed method integrates two‐stage neural networks with the Efficient Perspective‐n‐Point (EPnP) principle to determine the orientation and rotation angles, while an approximation principle based on feature point errors calculates linear positions. …”
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Suicide risk prediction for Korean adolescents based on machine learning by Haitao Wang, Han Yuan, Yunong Zhang, Qixuan Wang, Zeng Gao, Mujuan Zhao

“…Both the Expert Consultation Method (ECM) and Random Forest-Based Filter Feature Selection (RFFS) datasets revealed that the GBM model achieved the best results, with a predictive accuracy (ACC) of 88%, sensitivity (SENS) of 97%, specificity (SPEC) of 26%, positive predictive value (PPV) of 90%, negative predictive value (NPV) of 56%, and an area under the curve (AUC) of 83%. …”
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Embedded Machine Learning-Based Voltage Fingerprinting for Automotive Cybersecurity by Pierpaolo Dini, Michele Zappavigna, Ettore Soldaini, Sergio Saponara

“…This research presents the development and validation of an embedded system for real-time intrusion detection in automotive environments, leveraging voltage-based ECU fingerprinting. The proposed system integrates advanced machine learning algorithms, including SVM, ANN, and DT, optimized for anomaly detection, with linear SVM achieving the highest accuracy. …”
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Improving students' performance via case-based e-learning by Sebastian Ertl, Sebastian Ertl, Patricia P. Wadowski, Henriette Löffler-Stastka

“…Consequently, we evaluated the efficacy of a case-based e-learning approach.MethodThe impact of a case-based interdisciplinary e-learning environment with an integrated question/feedback system on medical students' academic performance was examined in a cross-sectional sample of different study years, longitudinally matched per academic year. …”
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Investigating the role of self-assessment in enhancing self-regulated learning amongst medical students in problem-based learning by Umatul Khoiriyah, Chris Roberts

“…This requires effective strategies for self-regulated learning (SRL). Problem-based learning (PBL) is one recognized method for fostering SRL skills. …”
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AN APPROACH TO MANAGING UNIVERSITY STUDENTS’ SELF-STUDY BASED ON INTERDISCIPLINARY E-PROJECTS by Yu. V. Krasavina, O. F. Shikhova

“…The article contributes to the problem of managing competency-based and professionally-oriented self-study for future teachers; the suggested method combines the advantages of project-based learning and the use of ICT.Aim. …”
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The implementation of teledentistry training in orthodontic practice: an explanatory sequential mixed-methods study by Supakit Peanchitlertkajorn, Charn Ngamdachakij, Boonsita Wongwatjana, Wichayaporn Jongpatranichpunth, Kawin Sipiyaruk

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IMPLEMENTASI PERENCANAAN STRATEJIK PEMBELAJARAN MELALUI PEMBELAJARAN BERDIFERENSIASI MENGGUNAKAN MEDIA BERBASIS TIK UNTUK MENINGKATKAN MINAT BELAJAR PESERTA DIDIK DIDIK by Badri Zaman, Abuy Abuy, Nelly Amalia, Ricky Yoseptry, Enyi Masrukoyah, Ira Setiani

“…The results of the study indicate that the implementation of differentiated learning using ICT-based media had a significant positive impact on increasing students' learning interest. …”
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Adaptive Improved Q-Learning Path Planning Algorithm Based on Obstacle Learning Matrix and Artificial Potential Field by Lieping Zhang, Hongyuan Chen, Xiaoxu Shi, Jianchu Zou, Yilin Wang

“…To address the issues of exploration imbalance and slow convergence speed in the Q-learning path planning algorithm, an adaptive improved Q-learning path planning algorithm based on an obstacle learning matrix and artificial potential field (APF) is proposed. …”
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Position-Aware Graph Neural Network for Few-Shot SAR Target Classification by Jia Zheng, Ming Li, Peng Zhang, Yan Wu, Hongmeng Chen

“…To address these issues, this article proposes a novel few-shot learning (FSL) method, called position-aware graph neural network (PA-GNN). …”
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The Impact of Online Learning on Digital Literacy Skills in Higher Education: Survey Methods and Test Analysis by Otang Kurniaman, Hadriana, Nur Islami, Zetra Hainul Putra, Zufriady

“…Digital literacy is someone’s ability to comprehend information as a learning source. The research uses a survey method in the form of a questionnaire and tests through SPSS. …”
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A mini-review of innovative learning methods in medical education: insights from African countries by Najoua Ghani, Mohamed Taiebine, Moulay Hassan Farih, Chakib Nejjari

“…Evidence suggests that these methods positively influence student learning outcomes, with research indicating enhancements in critical thinking, clinical reasoning, and self-directed learning capabilities. …”
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Prediction of additional hospital days in patients undergoing cervical spine surgery with machine learning methods by Bin Zhang, Shengsheng Huang, Chenxing Zhou, Jichong Zhu, Tianyou Chen, Sitan Feng, Chengqian Huang, Zequn Wang, Shaofeng Wu, Chong Liu, Xinli Zhan

“…Background Machine learning (ML), a subset of artificial intelligence (AI), uses algorithms to analyze data and predict outcomes without extensive human intervention. …”
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Bridging readiness and reasoning: A mixed methods study on learning readiness and students’ argumentation in mathematics by Nur Fauziyah, Erfina Jamil, Fatimatul Khikmiyah, Sarwo Edy

“…The results showed a positive correlation between learning readiness and students' argumentation ability in mathematics learning. …”
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A Qualitative Investigation of Team-Based Gamified Learning in an Online Environment by Yunjo An

“…Materials/methods – Game elements used for the team-based gamified learning experience included challenges, points, peer feedback and voting (social influence), and inter-team competition. …”
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