The Impact of ICT on Primary School Students’ Natural Science Learning in Support of Diversity: A Meta-Analysis by José Gabriel Soriano-Sánchez

“…In conclusion, ICT positively influences learning in Natural Sciences by increasing motivation among Primary School students with SENs. …”
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Developing an interpretable machine learning predictive model of chronic obstructive pulmonary disease by serum PFAS concentration by Xiaomei Shao, Ling Zhang, Yuting Wang, Youmei Ying, Xueqin Chen

“…While previous studies have examined the relationship between per- and polyfluoroalkyl substances (PFAS) and COPD, limited research has applied interpretable machine learning (ML) techniques to this association.MethodsWe investigated the association between PFAS exposure and COPD risk in 4,450 National Health and Nutrition Examination Survey (NHANES) participants from 2013 to 2018. …”
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Partnering With Youth to Enhance Healthcare Access and Experience: Lessons Learned From a Teen Advisory Group by Christi H. Esquivel, Sara A. Flores, Kristen Garcia, Whitney Garney, Kelly Wilson

“…ABSTRACT Introduction Youth are experts of their experiences and well‐positioned to be effective partners in innovation. A common method to engage youth in innovation is through an advisory board. …”
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Development of a clinical decision support system for breast cancer detection using ensemble deep learning by Jasjeet Kaur Sandhu, Chetna Sharma, Amandeep Kaur, Saroj Kumar Pandey, Anurag Sinha, J. Shreyas

“…This research discusses the creation of a unique Deep Learning (DL) Ensemble Deep Learning based on a Clinical Decision Support System (EDL-CDSS) that enables the precise and expeditious diagnosis of breast cancer. …”
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Imitation learning with artificial neural networks for demand response with a heuristic control approach for heat pumps by Thomas Dengiz, Max Kleinebrahm

“…This paper combines imitation learning based on an artificial neural network with an intelligent control approach for heat pumps. …”
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Rolling Bearing Dynamics Simulation Information-Assisted Fault Diagnosis with Multi-Adversarial Domain Transfer Learning by Zhe Li, Zhidan Zhong, Zhihui Zhang, Wentao Mao, Weiqi Zhang

“…To address the issues of negative transfer and reduced stability in transfer learning models for rolling bearing fault diagnosis under variable working conditions, an unsupervised multi-adversarial transfer learning fault diagnosis algorithm based on bearing dynamics simulation data is proposed. …”
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How do nursing students experience the clinical learning environment and respond to their experiences? A qualitative study by Majid Najafi Kalyani, Nahid Jamshidi, Zahra Molazem, Camellia Torabizadeh, Farkhondeh Sharif

“…Identifying nursing students’ experiences is essential to develop interventions to reduce challenges.Objective This study aimed to explore nursing students’ experiences in a clinical learning environment and the way they responded to these experiences.Design The present study was conducted based on the qualitative research design of the grounded theory methodology.Setting This study was conducted at schools of nursing in academic settings in Iran.Participants The participants included 19 nursing students, 4 nursing instructors and 3 clinical nurses.Methods The data were collected using semistructured interviews, field notes and observation, and were analysed using Strauss and Corbin’s approach.Results Students, as a result of the inadequacy of the educational environment, were faced with ‘confusion of identity’, stating this as their main concern. …”
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Implementasi Model Pembelajaran Klasik dan Model Pembelajaran Kelompok PAUD Bintang Ananda Botoran Tulungagung by Siti Istatik Choiroyaroh

“…Early childhood education should have optimal, effective, efficient, productive, and accountable policies and coordinate well with government, family, and community support to produce positive and maximum impacts. This study aims to explain the conditions of learning management at PAUD Bintang Ananda, which experiences differences in learning models applied in institutions; institutions apply two learning models, namely classical and group. …”
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A multi-data fusion deep learning model for prognostic prediction in upper tract urothelial carcinoma by Hongdi Sun, Siping Chen, Yongxing Bao, Fengyan You, Honghui Zhu, Xin Yao, Lianguo Chen, Lianguo Chen, Jiangwei Miao, Fanggui Shao, Fanggui Shao, Xiaomin Gao, Binwei Lin

“…The model’s prognostic performance was compared with two unimodal models—ImageNet (CT-based) and ClinicalNet (clinical data-based)—and traditional clinical parameters including pathological T stage. …”
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Model of Arabic Language Learning Management in Child-Friendly Schools for the Development of Character Education in the Independent Curriculum by Nasarudin Nasarudin, Nurjannah Nurjannah, Muhirdan Muhirdan, Ahmad Helwani Syafii, Husnan Husnan, Henny Marlina

“…The Do stage involves implementing the module with a differentiated approach and learning methods that emphasize character. In Check, evaluation involves principals, teachers, and students, ensuring learning effectiveness and positive perceptions of Arabic. …”
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Role of Artificial Intelligence and Deep Learning in Easier Skin Cancer Detection through Antioxidants Present in Food by Sreevidya R. C., Jalaja G, Sajitha N, D. Lakshmi Padmaja, S. Nagaprasad, Kumud Pant, Yekula Prasanna Kumar

“…There are various antioxidants like vitamins C, E, and A, zinc, and selenium present in various foods that can be helpful in preventing skin cancer. “Deep Learning” (DL) is an effective method to detect cancerous lesions. …”
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Predictive Modeling of Acute Respiratory Distress Syndrome Using Machine Learning: Systematic Review and Meta-Analysis by Jinxi Yang, Siyao Zeng, Shanpeng Cui, Junbo Zheng, Hongliang Wang

“…The findings will provide evidence-based insights to support the development of more accurate and effective ARDS prediction tools. …”
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Approaches used to prevent and reduce the use of restrictive practices on adults with learning disabilities: a realist review by Joy Duxbury, Alina Haines-Delmont, John Baker, Peter Baker, Gary Bourlet, Elaine Craig, James Ridley, Rachel Whyte, Beth Morrison, Michaela Thomson, Anthony Tsang, Tella Lantta

“…In line with realist methods, eight context–mechanism–outcome configurations and an overarching programme theory were used to explain the why and how of preventing and reducing the use of restrictive practices for people with a learning disability. …”
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Empirical Study of Differentiated Learning Using The Moodle Platform on Personalized Informatics Subjects in Vocational High Schools by Jajang Kusnendar, Deni Darmawan, Rusman Rusman, Indriyani Rachman

“…The results showed that: 1) differentiated learning patterns were found, where each student had varied learning patterns and preferences on the teaching material provided; 2) process differentiation successfully facilitates diverse student learning abilities to achieve learning completeness; 3) Students respond positively to differentiated learning based on: distinctive learning preferences, material availability, readiness to learn, learning speed, and opportunity to complete learning. …”
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Self-assessment and learning motivation in emergency point-of-care ultrasound: an online pilot investigation in German physicians by Joachim Bansbach, Michael Bentele, Matthias Bollinger, Stefanie Bentele, Ronny Langenhan, Bianka Gerber, Milena Trifunovic-Koenig, Stefan Bushuven

“…Overplacing oneself above peers negatively correlated with intrinsic learning motivation and identified regulation and positively correlated to amotivation. …”
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Single-cell and machine learning approaches uncover intrinsic immune-evasion genes in the prognosis of hepatocellular carcinoma by Jiani Wang, Xiaopeng Chen, Donghao Wu, Changchang Jia, Qinghai Lian, Yuhang Pan, Jiumei Yang

“…To address these issues, single-cell technology and machine learning methods have emerged as a promising approach to identify genes associated with immune escape in HCC. …”
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Feasibility of implementing a rapid-learning methodology to inform radiotherapy treatments: key professional stakeholders’ views by Corinne Faivre-Finn, Kevin Franks, Fiona McDonald, David P French, Daniel Johnson, Arbaz Kapadi, Gareth Price, Rebecca Holley, Kate Wicks, Kathryn Banfill, Gareth Webster

“…This study investigated key professional stakeholders’ perceptions and opinions of rapid-learning and real-world data (RWD).Methods and analysis Twenty-three interviews were conducted with key professional stakeholders based across five UK radiotherapy cancer centres. …”
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Training Socially-Conscious Dentists: Development and Integration of Community Service-Learning in Dental Curricula in Ontario, Canada by Abbas Jessani, Alexia Athanasakos, Randy Peltz, Rifat Hussain, Amani Radhaa, Martin McIntosh, Althaf Lathif, Sarah McLean

“…Methods: The CSL programme was developed utilizing Yoder's framework for service-learning and Lave and Wenger's framework for situated learning. …”
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Learning teamworking and non-technical skills: a pilot study of a postgraduate course at the University of Florence by Veronica Verde, Yari Bardacci, Lorenzo Ballerini, Samuele Baldassini Rodriguez, Chiara Balestri, Paolo Iovino, Simone Belli, Stefano Bambi

“…In healthcare systems, NTS exert positive effects on patients’ safety and healthcare professionals’ efficiency. …”
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Predicting pediatric age from chest X-rays using deep learning: a novel approach by Maolin Li, Jiang Zhao, Huanhuan Liu, Biao Jin, Xuee Cui, Dengbin Wang

“…Materials and methods We developed a ResNet-based deep neural network model enhanced with Coordinate Attention mechanism to predict pediatric age from chest X-rays. …”
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