Training academic staff for effective feedback in workplace-based assessment: a study in Bhutan by Sontosh Mukhia, Karma Tenzin

“…Abstract Introduction The feedback plays a critical role in competency-based education in both undergraduate and Postgraduate medical education. …”
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Smart Learning from a Young Age : A Systematic Review of Digital Technology Integration for Cognitive Development by Nabil Fikri Adam, Suwito Eko Pramono, Arief Yulianto, Bambang Subali, Nuni Widiarti

“…The results revealed that digital technology integration positively impacts cognitive learning outcomes, with video and animation-based approaches being most prevalent (26.92%), followed by virtual/augmented reality, interactive applications, and educational games (19.23% each). …”
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Predictive model for sarcopenia in chronic kidney disease: a nomogram and machine learning approach using CHARLS data by Renjie Lu, Shiyun Wang, Pinghua Chen, Fangfang Li, Fangfang Li, Pan Li, Qian Chen, Xuefei Li, Fangyu Li, Suxia Guo, Jinlin Zhang, Jinlin Zhang, Dan Liu, Zhijun Hu

“…This research aimed to create and assess a predictive model for the risk of sarcopenia in CKD patients, utilizing data obtained from the China Health and Retirement Longitudinal Study (CHARLS).MethodsSarcopenia was diagnosed based on the Asian Working Group for Sarcopenia (AWGS 2019) criteria, including low muscle strength, reduced physical performance, and low muscle mass. …”
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Unraveling and rectifying the free-riding behavior among students in university flipped classrooms: a uninorm DEMATEL method by Shiyu Yan, Lisheng Jiang, Zhili Zuo, Lixuan An, Li Wang

“…Secondly, the unfairness indices of groups and the discount parameters of students are determined based on the comprehensive index. The discounted scores are employed to modify students' achievement to ensure fairness.ResultsA case study involving 57 students is presented to demonstrate the applicability of the proposed method, and a sensitivity analysis is conducted to assess its robustness. …”
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Integrating academic and professional integrity: a co-designed serious game for nursing students - a multi-methods study by Laura Creighton, Gary Mitchell, Conor Hamilton, Stephanie Craig, Patrick Stark, Nuala McLaughlin-Borlace, Christine Slade, Christine Brown Wilson

“…Suggesting that the integration of case-based learning within a serious game offers a proactive, rather than punitive, approach to academic misconduct education, with potential applicability across diverse cultural and professional contexts.…”
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Scene Target 3D Point Cloud Reconstruction Technology Combining Monocular Focus Stack and Deep Learning by Yanzhu Hu, Yingjian Wang, Song Wang

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Evolution and model prediction of mechanical ventilation temperature field in high-geotemperature tunnels: Experimental analysis and machine learning by Feng Huang, Song Wang, Shuping Jiang, Dong Yang, Zheng Hu, Aichen Zheng

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Integration of Islamic-based anti-corruption education in Al Qur’an and hadith study courses by Zeid B Smeer, Mubasyiroh Mubasyiroh, Hamim Hamim, Inayatur Rosyidah

“…Anti-corruption education from an Islamic perspective for students is an alternative in eradicating Corruption. integration education anti-Corruption in the Qur'an and Hadith courses is education anti-Corruption merges in Al-Qur'an and Hadith courses through development Theory because of course part the material contain payload score and behavior anti-Corruption, as well as through development learning methods and media. Based on data processing obtained for category moral knowing It was found that the ICP PAI students of UIN Maliki Malang class of 2020 reached 82%. …”
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Integrated and improved YOLOv8 and triangulated network method for extracting indicators in open-pit mine mining areas by LI Tianwen, LI Gongquan, LI Juntao

“…The research on remote sensing imagery of open-pit mines based on deep learning has provided a direction for the rapid identification and extraction of open-pit mining areas. …”
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Sex estimation with parameters of the facial canal by computed tomography using machine learning algorithms and artificial neural networks by Yusuf Secgin, Seren Kaya, Oğuzhan Harmandaoğlu, Oğuzhan Öztürk, Deniz Senol, Ömer Önbaş, Nihat Yılmaz

“…Conclusions FN-centered morphometric measurements show high accuracy in sex determination and may aid in understanding FN positioning across sexes and populations. These findings may support rapid and reliable sex estimation in forensic investigations—especially in cases with fragmented craniofacial remains—and provide auxiliary diagnostic data for preoperative planning in otologic and skull base surgeries. …”
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Comparative evaluation of spatiotemporal methods for effective dengue cluster detection with a case study of national surveillance data in Thailand by Chawarat Rotejanaprasert, Kawin Chinpong, Andrew B. Lawson, Richard J. Maude

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Reexamining the Evidence-Based Practice Attitude Scale-36 (EBPAS-36) in a U.S. sample of trauma-focused treatment providers by Joshua P. Mersky, ChienTi Plummer Lee, Edwin Bacalso, Xiyao Liu

“…Abstract Background Mental health providers’ attitudes toward evidence-based practice are likely to influence what interventions they learn, implement, and sustain over time. …”
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CR-Mask RCNN: An Improved Mask RCNN Method for Airport Runway Detection and Segmentation in Remote Sensing Images by Meng Wan, Guannan Zhong, Qingshuang Wu, Xin Zhao, Yuqin Lin, Yida Lu

“…Airport runways, as the core part of airports, belong to vital national infrastructure, and the target detection and segmentation of airport runways in remote sensing images using deep learning methods have significant research value. Most of the existing airport target detection methods based on deep learning rely on horizontal bounding boxes for localization, which often contain irrelevant background information. …”
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U-net based approach for pectoralis muscle segmentation in digital mammography by Francesca Angelone, Alfonso Maria Ponsiglione, Roberto Grassi, Francesco Amato, Mario Sansone

“…This study aims to propose an automatic breast segmentation algorithm that combines traditional methods with Deep Learning methods limited only to the border region between the muscle and the breast. …”
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Community Health Worker Diabetes Prevention Awareness Training in an Immersive Virtual World Environment: Mixed Methods Pilot Study by Laurie Ruggiero, Lauretta Quinn, Amparo Castillo, Colleen Monahan, Leticia Boughton Price, Wandy Hernandez

“…One remote approach, immersive 3D virtual worlds (VW) offer a unique approach to providing remote training incorporating engaging interactive contextual learning opportunities. ObjectiveThis study aimed to implement and evaluate an internet-based 3D VW model to remotely deliver an adapted CHW training program on diabetes prevention awareness for racial-ethnic minority communities. …”
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Advancing analytical and graphical methods for binary and ternary mixtures: The toxic interactions of divalent metal ions in human lung cells by James Y. Liu, Jonathan M. Beard, Saber Hussain, Christie M. Sayes

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Lessons Learned From Covid-19 Pandemia: Pregnancy Anxiety Level Increases During A Life Threatening Period by Erdoğan Aslan, Merve Çakır Köle, Hakan Demir, Gökşen Görgülü, Emre Köle, Lale Aksoy

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Development and validation of a comprehensive tool to study the various elements influencing the utilization of E-learning among undergraduate health professions students by Archana Prabu Kumar, Prabu Kumar Chokkalingam Mani, Komal Atta, Abirami Omprakash, K. Maheshkumar, Hany Atwa, K. N. Maruthy, Padmavathi R.

“…The developed CKAPQ provides a new, standardized method to evaluate knowledge, attitudes, and practices related to E-learning among medical and dental students.…”
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Patient perspectives on AI-based decision support in surgery by Corrette Ploem, Saskia Haitjema, Geert Kazemier, Olga Damman, Sara Ben Hmido, Houssam Abder Rahim, Freek Daams

“…The associations in the code tree were established based on a co-occurrence table. The patient sample size was determined using a saturation analysis.Results A study with n=19 participants across four focus groups and seven interviews found a generally positive perception regarding the use of IPML models in CRS. …”
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Combining machine learning and dynamic system techniques to early detection of respiratory outbreaks in routinely collected primary healthcare records by Dérick G. F. Borges, Eluã R. Coutinho, Thiago Cerqueira-Silva, Malú Grave, Adriano O. Vasconcelos, Luiz Landau, Alvaro L. G. A. Coutinho, Pablo Ivan P. Ramos, Manoel Barral-Netto, Suani T. R. Pinho, Marcos E. Barreto, Roberto F. S. Andrade

“…Deviations from historical trends in encounter numbers can provide valuable insights into emerging diseases with the potential to trigger widespread outbreaks. Methods Unsupervised machine learning methods and dynamical systems concepts were combined into the Mixed Model of Artificial Intelligence and Next-Generation (MMAING) ensemble, which aims to detect early signs of outbreaks based on primary healthcare encounters. …”
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