Rapid Path Planning Algorithm for Percutaneous Rigid Needle Biopsy Based on Optical Illumination Principles by Jian Liu, Shuai Kang, Juan Ren, Dongxia Zhang, Bing Niu, Kai Xu

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Virtual reality for education on infection prevention and control: the impact on medical students’ knowledge, attitudes and practices by Bente Schippers, Olga Coenen, Franka Luk, Mark Graner, Frans van Hoek, Nike Stikkelbroeck, Machteld Dronkers, Edmée Bowles, Alma Tostmann

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Сoronavirus Zigzags of Electronic Distance Learning by A. V. Solovov, A. A. Menshikova

“…The purpose of this article is to analyze the didactic aspects of the experience of using EDL methods and technological tools during a pandemic, to assess the potential positive and real negativity of this process, to develop recommendations on the rational use of modern virtual learning environments. …”
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AI-Based Prediction of Visual Performance in Rhythmic Gymnasts Using Eye-Tracking Data and Decision Tree Models by Ricardo Bernardez-Vilaboa, F. Javier Povedano-Montero, José Ramon Trillo, Alicia Ruiz-Pomeda, Gema Martínez-Florentín, Juan E. Cedrún-Sánchez

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Empathy Training: Methods, Evaluation Practices, and Validity by Tony Chiu Ming Lam, Klodiana Kolomitro, Flanny C. Alamparambil

“…These findings suggest that regardless of the training method, individuals can learn about the concept of empathy. …”
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Multi-strategy collaborative optimization of gravitational search algorithm by Zhonghua Yang, Yuanli Cai, Ge Li, Peng Wang, Yu Chen

“…Finally, the lens-imaging opposition-based learning strategy generates opposite solutions for particles at different stages, increasing population diversity, expanding the search range, and enhancing the global search performance of the algorithm. …”
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Neuropedagogy and Neuroimaging of Artificial Intelligence and Deep Learning by Claudia De Barros Camargo , Antonio Hernández Fernández

“…This study investigates the integration of neuropedagogy, neuroimaging, artificial intelligence (AI), and deep learning in educational systems. The research aims to elucidate how these technologies can be synergistically applied to optimize learning processes based on individual neurocognitive profiles, thereby enhancing educational effectiveness. …”
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Teaching English as a Foreign Language Using Multiple Intelligences, Cooperative Learning and Taking into Account the Pupils’ Perceptual Learning Styles by Imene CHEBRI

“…Based on the results of our study, secondary school pupils can improve their achievements and their English language proficiencies through the implementation of new teaching methods based on cooperative learning, multiple intelligences theory and learners’ perceptual learning styles. …”
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Abnormal Sound Detection of Wind Turbine Gearboxes Based on Improved MobileFaceNet and Feature Fusion by Yuelong Liang, Haorui Liu, Yayu Chen

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Comparison of machine learning models for coronavirus prediction by B. K. Amos, I. V. Smirnov, M. M. Hermann

“…The comparison is based on individuals in class 1, i.e., those with a positive test. …”
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TransTab: A transformer-based approach for table detection and tabular data extraction from scanned document images by Yongzhou Wang, Wenliang Lv, Weijie Wu, Guanheng Xie, BiBo Lu, ChunYang Wang, Chao Zhan, Baishun Su

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Class Incremental Learning With Large Domain Shift by Kamin Lee, Hyoeun Kim, Geunjae Choi, Hyejeong Jeon, Nojun Kwak

“…We address an important and practical problem facing deep-learning-based image classification: class incremental learning with a large domain shift. …”
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Linking Electrocardiogram and Echocardiogram: Comparing Classical Machine Learning and Deep Learning Neural Networks for the Detection of Regional Wall Motion Abnormalities by Shantanu M. Joshi, Hana R. Shaik, Shivam Rai Sharma, Philip Strong, Uma Srivatsa, Imo Ebong, Hyoyoung Jeong, Chen-Nee Chuah, Lihong Mo

“…Our study aimed to predict RWMA using both classical machine learning (ML) methods and a one-dimensional convolutional neural network (1D CNN) model on the 12-lead ECG data from 3,750 unique patients provided by the Nightingale Open Science platform. …”
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A hybrid approach using support vector machine rule-based system: detecting cyber threats in internet of things by M. Wasim Abbas Ashraf, Arvind R. Singh, A. Pandian, Rajkumar Singh Rathore, Mohit Bajaj, Ievgen Zaitsev

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Artificial intelligence-based prediction of second stage duration in labor: a multicenter retrospective cohort analysisResearch in context by Xiaoqing Huang, Xiaodan Di, Suiwen Lin, Minrong Yao, Suijin Zheng, Shuyi Liu, Wayan Lau, Zhixin Ye, Zilian Wang, Bin Liu

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Using baseline MRI radiomics to predict the tumor shrinkage patterns in HR-Positive, HER2-Negative Breast Cancer by Lijia Wang, Yongchen Wang, Li Yang, Jialiang Ren, Qian Xu, Yingmin Zhai, Tao Zhou

“…IntroductionThis study aimed to develop and validate a predictive model for tumor shrinkage patterns in hormone receptor-positive, HER2-negative (HR+/HER2-) breast cancer patients undergoing neoadjuvant chemotherapy (NAC).MethodsA retrospective analysis was conducted on 227 HR+/HER2- breast cancer patients with a desire for breast conservation, examining their clinicopathological characteristics, traditional MRI features, and radiomics features. …”
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Integration of YOLOv9 Segmentation and Monocular Depth Estimation in Thermal Imaging for Prediction of Estrus in Sows Based on Pixel Intensity Analysis by Iyad Almadani, Aaron L. Robinson, Mohammed Abuhussein

“…We then introduce a classification approach that differentiates between estrus and non-estrus regions based on the mean pixel intensity of the vulva. This classification method involves calculating Euclidean distances between new data points and reference points from two datasets: one for “estrus” and the other for “non-estrus”. …”
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Develoment of The Computer Simulation of Oscillation in Physics Learning by Y Sumardi, A F Amalia, U N Prabowo

“…This research aimed to develop the computer simulation of oscillation in physics learning by using MATLAB. The use of simulations within teaching process had a positive impact on students’ being able to predict and explain the phenomena. …”
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Prenatal detection of congenital heart defects using the deep learning-based image and video analysis: protocol for Clinical Artificial Intelligence in Fetal Echocardiography (CAIF... by Aris Papageorghiou, Aris T Papageorghiou, David Black, Lawrence Impey, Rachel Craik, Alison Noble, Rahul Ahuja, Christina Aye, Christos Ioannou, Beverly Tsai-Goodman, Kevin Roman, Anupama Nair, Jessica Farmer, J Alison Noble, Makrina Savvidou, Bernadette Brent, Julene Carvalho, Olga Patey, Netzahualcoyotl Hernandez-Cruz, Elena D’Alberti, Bojana Salovic, Theophilus Adu-Bredu, Ilaria Bo, Angelo Cavallaro, FabricioDa SivaCosta, Emma Eccleston, Joanne Everingham, CristianeDe FreitasPaganoti, Eleni Fotaki, Tyrrell Hatch, Joanna Kellett, Karina Lopes, Sally Mahler, Risa Miyazaki Sankar, Divyanshu Mishra, Jennifer Norville, Olivia Nunn, Lola Oshodi, Stavros Polyviou, Lorjah Rajah, Daifenir Rodriguezde LaCruz, Katja Shipp, Bethany Shobbrook, Sophie Tooth, Dimuthu Weerasuriya, Qianye Yang, Yingyu Yang

“…Research has shown that deep learning-based or more general artificial intelligence (AI) models can support the detection of fetal CHDs more rapidly than humans performing ultrasound scan. …”
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Tourist Destination Recommendations Using Deep Learning by Amarita Ritthipakdee, Chartchai Leenawong

“…Leveraging this infrastructure, this study proposes a deep learning-based model designed to classify tourists into five categories: Nature Tourists, Cultural Tourists, Shopping Tourists, Historical Tourists, and Industrial Tourists. …”
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