Performance of emergency triage prediction of an open access natural language processing based chatbot application (ChatGPT): A preliminary, scenario-based cross-sectional study by İbrahim Sarbay, Göksu Bozdereli Berikol, İbrahim Ulaş Özturan

“…OpenAI’s ChatGPT is a supervised and empowered machine learning-based chatbot. The aim of this study was to determine the performance of ChatGPT in emergency medicine (EM) triage prediction. …”
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Deep Learning Technique for Automatic Segmentation of Proximal Hip Musculoskeletal Tissues From CT Scan Images: A MrOS Study by Mahdi Imani, Jared Buratto, Thang Dao, Erik Meijering, Sara Vogrin, Timothy C. Y. Kwok, Eric S. Orwoll, Peggy M. Cawthon, Gustavo Duque

“…Conclusion Our deep learning–based technique offers a fast and accurate method for segmentation and quantification of musculoskeletal tissues in proximal hip, with potential clinical value.…”
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The effects of perceived distributed leadership on teacher professional development among primary school teachers: The mediating role of teacher professional learning community by Xiaomin Yang, Yuan-Cheng Chang

“…The research results indicate that both distributed leadership and teacher professional learning communities can positively predict teacher professional development, and distributed leadership can positively predict teacher professional learning communities; The teacher professional learning community plays a completely mediating role between distributed leadership and teacher professional development.…”
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Basic Research on the Development of an Automatic Heart Sound Diagnosis System - Analysis of Heart Sounds for Learning Policy and Experiment for the Prototype of the Auscultation P... by Hirotoshi Hishida, Koichi Tokuuye, Keiko Hishida, Hayato Tojo, Yasuhiro Hishida, Tomomi Koide

“…A design policy was established for a specific data flow and learning method for the automatic heart-sound diagnosis system under development. …”
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The Wide Swath Significant Wave Height: An Innovative Reconstruction of Significant Wave Heights From CFOSAT’s SWIM and Scatterometer Using Deep Learning by J. K. Wang, L. Aouf, A. Dalphinet, Y. G. Zhang, Y. Xu, D. Hauser, J. Q. Liu

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An enhanced machine learning approach with stacking ensemble learner for accurate liver cancer diagnosis using feature selection and gene expression data by Amena Mahmoud, Eiko Takaoka

“…The stacking ensemble achieved an accuracy of (97%), outperforming individual machine learning algorithms and traditional diagnostic methods. …”
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Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…This study facilitates the data-driven design of novel cast TiAl alloys by systematically investigating the critical elements and their interactions affecting room-temperature (RT) tensile properties by the machine learning method based on SHAP analysis. Comparative analysis of three algorithms within the training dataset proved the random forest regression (RFR) as the optimal modeling approach. …”
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Lane Detection Based on CycleGAN and Feature Fusion in Challenging Scenes by Eric Hsueh-Chan Lu, Wei-Chih Chiu

“…Image-based deep learning is currently the most advanced method for lane detection. …”
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The effects of community-based education programs on empathy, emotional intelligence, and caring behaviors among nursing students: a scoping review by Ma Jing, Ma Jing, Pinglei Chui, Mei Chan Chong, Tang Maoting

“…IntroductionCommunity-based learning approaches are gaining recognition in nursing education as a means to address the needs of aging societies by fostering empathy, emotional intelligence, and caring behaviors among nursing students. …”
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Research on music education simulation based on interactive experience of virtual and reality by Wanchen Li

“…The results show that most students have a positive attitude towards this novel teaching method, and they believe that this method can better stimulate the interest in learning and improve the learning effect. …”
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Object Detection Algorithm Based on Feature Enhancement and Anchor-object Matching by LI Cheng-yan, ZHAO Shuai, CHE Zi-xuan

“…Anchor evaluation score, in continuous iterative learning, the model parameters, Anchor position coordinates and classification confidence are continuously optimized. …”
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Surface-Enhanced Raman Scattering Combined with Machine Learning for Rapid and Sensitive Detection of Anti-SARS-CoV-2 IgG by Thais de Andrade Silva, Gabriel Fernandes Souza dos Santos, Adilson Ribeiro Prado, Daniel Cruz Cavalieri, Arnaldo Gomes Leal Junior, Flávio Garcia Pereira, Camilo A. R. Díaz, Marco Cesar Cunegundes Guimarães, Servio Túlio Alves Cassini, Jairo Pinto de Oliveira

“…This work reports an efficient method to detect SARS-CoV-2 antibodies in blood samples based on SERS combined with a machine learning tool. …”
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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…Method Peripheral blood samples from breast cancer screening positive and negative people were used for small RNA sequencing of plasma exosomes. …”
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Effects of Computer-Assisted Working Memory Training Programme on Working Memory Ability and Mathematical Performance of Children at Risk of Mathematical Learning Difficulties by Kamyar Azimi, Manijeh Shehniyailagh, Alireza Hajiyakhchali, Maneli Shehni Karamzadeh

“…Most importantly, it is uncertain whether the positive effects observed in laboratory settings can be replicated in real-world learning environments. …”
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A pose generation model for animated characters based on DCNN and PFNN by Boli Wang

“…The animation character generation method includes data collection and the application after data collection, which shows the various roles that deep learning technology can play in the field of computer graphics animation, and also provides excellent solutions for other computer graphics problems.…”
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Dual conditional GAN based on external attention for semantic image synthesis by Gang Liu, Qijun Zhou, Xiaoxiao Xie, Qingchen Yu

“…Although the existing semantic image synthesis methods based on generative adversarial networks (GANs) have achieved great success, the quality of the generated images still cannot achieve satisfactory results. …”
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Understanding adaptations in a community-vetted COVID-19 testing program by Breanna J. Reyes, Stephenie Tinoco Calvillo, Angel Lomeli, Angel Lomeli, Arleth A. Escoto, Maria Linda Burola, Kelli L. Cain, Linda Salgin, Linda Salgin, Maria Balbuena-Bojorquez, Anne-Marie Engler, Marva Seifert, Louise C. Laurent, Nicole A. Stadnick, Nicole A. Stadnick, Nicole A. Stadnick, Borsika A. Rabin, Borsika A. Rabin

“…Here, we report processes used for tracking and evaluating adaptations made during the CO-CREATE project, which aimed to address COVID-19 testing disparities in the San Ysidro US/Mexico border community.MethodsThe study utilized a longitudinal, prospective, mixed methods approach to systematically document and assess adaptations across the pre-implementation, early and mid/late-implementation phases of the project. …”
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A novel Swin transformer based framework for speech recognition for dysarthria by Rabbia Mahum, Ismaila Ganiyu, Lotfi Hidri, Ahmed M. El-Sherbeeny, Haseeb Hassan

“…Several previous studies have concentrated on detecting dysarthria speech using machine learning-based methods. However, the false positive rate is high due to the varying nature of speech and environmental factors such as background noise. …”
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Evaluation of Arabic lesson teaching in higher education based on the Kirkpatrick model by Ali Akbar Mollaie, Mohammad Aslam Raiesi

“…Abstract The aim of the research was to evaluate the teaching of Arabic in higher education institutions in Tehran based on the Kirkpatrick model. The research method was applicable in terms of its purpose, and descriptive-survey in terms of data collection, using a questionnaire as the tool. …”
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Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopy by Yasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, Hirokazu Fukidome, Hideitsu Hino, Masato Okada

“…By reconstructing high-resolution images from multiple low-resolution ones, exposure time is minimized, reducing radiation effects, thermal drift, and sample degradation while preserving spatial resolution. Unlike deep learning-based superresolution methods, which overlook positional misalignment, our approach treats positional shifts as known control parameters, enhancing superresolution accuracy with a small, noisy dataset. …”
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