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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Understanding the Impact of Street Environments on Traffic Crash Risk from the Perspective of Aging People: An Interpretable Machine Learning Approach by Ketong Shen, Jian Liu, Xintao Liu

“…Interpretable machine learning methods are then employed to identify key environmental contributors and to compare their spatial contribution patterns across age groups. …”
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Ge-SAND: an explainable deep learning-driven framework for disease risk prediction by uncovering complex genetic interactions in parallel by Lihang Ye, Liubin Zhang, Bin Tang, Junhao Liang, Ruijie Tan, Hui Jiang, Wenjie Peng, Nan Lin, Kun Li, Chao Xue, Miaoxin Li

“…Applied to simulated datasets and UK Biobank cohorts for Crohn’s disease, schizophrenia, and Alzheimer’s disease, Ge-SAND achieved up to a 20% improvement in AUC-ROC compared to mainstream methods. Beyond its predictive accuracy, through self-attention-based interaction networks, Ge-SAND provided insights into large-scale genotype relationships and revealed genetic mechanisms underlying these complex diseases. …”
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Using the Practical, Robust Implementation and Sustainability Model to identify implementation determinants of a statewide diabetes learning collaborative in Kentucky by Aaron J. Kruse-Diehr, Borsika A. Rabin, Jessica Elliott, Vance Drakeford, Laura Wright, Brent McKune, Russell E. Glasgow, Key C. Douthitt, James W. Keck, Mary E. Lacy

“…Methods Semi-structured Zoom interviews were conducted with three discrete groups of learning collaborative participants (N = 26): (1) clinic practitioners and support staff (n = 13); (2) health department educators (n = 8) who received DSMES referrals from clinics; and (3) staff of a regional extension center (n = 5) who facilitated the collaboratives. …”
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The impact of perceived teacher support on students’ learning approach: the chain mediating role of academic engagement and achievement goal orientation by Yaqi Zhang, Xiangli Guan, Jingjing Wang, Sumei Yin, Xuejiao Li, Yang Li, Mary C. Jobe, Md Zahir Ahmed

“…A conceptual model between these variables was constructed based on existing research and Personal Investment Theory.MethodsSelf-report data from 543 Chinese university undergraduates was analyzed through whole group sampling to verify the model and clarify the underlying mechanisms by which perceived teacher support influences university students’ learning approach. …”
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Develop and validate a machine learning model to predict the risk of persistent pain after percutaneous transforaminal endoscopic discectomy by Jun Yuan, Jun Fu

“…This study aims to utilize machine learning models to predict persistent pain, identify key influencing factors, and construct a risk model to assess the likelihood of persistent pain.MethodsWe first compared baseline characteristics and pathological indicators between patients who developed persistent pain and those who did not after PTED. …”
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Exploring the determinants on continuance participation of college students toward blended learning: the stimulating role of course characteristics and instructor support by Maoyan She, Yiyang Xu, Zhigang Li, Die Hu

“…Therefore, it is necessary to deeply analyze the question: “What factors will influence college students’ continuance behavior in blended learning (CBBL)?”MethodsBased on the stimulus-organism-response (SOR) framework and social cognitive theory, this study constructs an integrated model of “Contextual facilitators–Individual characteristics–Continuance behavior,” to examine the relationships among the blended course characteristics (BCC), instructor support (IST), individual attributes, such as learning motivation (LM), self-efficacy (SEF) and learning engagement (LET), and college students’ CBBL. …”
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Gadoxetic acid-enhanced MRI for identifying cholangiocyte phenotype hepatocellular carcinoma by interpretable machine learning: individual application of SHAP by Wei Liu, Zhiping Cai, Yifan Chen, Xingqun Guan, Jieying Feng, Haixiong Chen, Baoliang Guo, Fusheng OuYang, Chun Luo, Rong Zhang, Xinjie Chen, Xiaohong Li, Cuiru Zhou, Shaomin Yang, Ziwei Liu, Qiugen Hu

“…This study aims to develop and validate an optimal machine learning model to predict cholangiocyte phenotype HCC based on T1 mapping gadoxetic acid-enhanced MRI and to implement individual applications via the Shapley Additive explanation (SHAP). …”
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Exploring the Correlation between Binaural Processing Abilities and Auditory Processing Domains Questionnaire Scores in Children with Specific Learning Disabilities by Marziyeh Moallemi, Nariman Rahbar, Mohsen Ahadi, Mohammad Maarefvand

“… Background and Aim: A Specific Learning Disability (SLD) is a neurological disorder thought to arise from dysfunctions within the central nervous system. …”
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Development and Validation of a Cost-Effective Machine Learning Model for Screening Potential Rheumatoid Arthritis in Primary Healthcare Clinics by Wu W, Hu X, Yan L, Li Z, Li B, Chen X, Lin Z, Zeng H, Li C, Mo Y, Wu Y, Wang Q

“…Our findings contribute positively and are poised to elevate prospective RA management, fostering improvements in healthcare sector responsiveness and resource efficiency.Keywords: rheumatoid arthritis, machine learning, primary health care…”
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Students’ experiences of interprofessional learning by simulating the Swedish concept of coordinated individual care in primary healthcare: a qualitative analysis by Pernilla Alencar Siljehag, Sofie Guldbrand, Helena Sohlman, Marina Taloyan

“…and (2) What is the novelty of using the CIP meeting with regards to the ICCAS (Interprofessional Collaborative Competency Attainment Survey) - self-assessment scale of IPL competences? Method and material The current study is based on a qualitative evaluation of 12 learning activities carried out over a one-year period. …”
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Predicting forest above-ground biomass using SAR imagery and GEDI data through machine learning in GEE cloud by Chiranjit Singha, Kishore Chandra Swain, Satiprasad Sahoo, Ayad M. Fadhil Al-Quraishi, Joseph Omeiza Alao, Hussein Almohamad, Mohamed Fatahalla Mohamed Ahmed, Hazem Ghassan Abdo

“…The Random forest-based Boruta method was used to examine the importance of multiple factors contributing to the prediction’s accuracy. …”
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The Mediating Role of the Principal–Teacher Relationship in Innovative School Leadership and Teacher Professional Learning According to Turkish Teachers’ Perceptions by Mehmet Özdoğru, Yurdagül Doğuş, Muhammet İbrahim Akyürek

“…Data obtained from 357 teachers working in high schools in Eskişehir, Türkiye, were examined with a mediation analysis based on the bootstrap method. The findings showed that teachers perceived their professional learning highly, school administrators perceived innovative school leadership characteristics highly, and principal–teacher relationships had a significant effect. …”
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The effect of educational philosophies on learning principles with the mediating role of epistemological beliefs among faculty members of University of Sistan and Baluchestan by sara jenabadi, Vali Mehdinezhad

“…The aim of this study was to investigate the effect of faculty members'educational philosophies on learning principles with the mediating role of epistemological beliefs.The research method used in this study was descriptive-correlational. …”
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Pembentukan Karakter melalui Pembelajaran Ilmu Pengetahuan Sosial (IPS) by Rintati Megawati, Tutuk Ningsih

“…This paper aims to examine the formation of character through social studies learning. This study uses a qualitative-descriptive method to explore the values and character of education in Social Sciences (IPS) subjects with the researcher as the main instrument. …”
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Machine learning for post-diploma educational and career guidance: a scoping review in AI-driven decision support systems by Flavio Manganello, Elisa Rasca, Alberto Villa, Andrea Maddalena, Giannangelo Boccuzzi

“…While several contributions report positive technical performance, evidence on educational effectiveness and user impact is limited. …”
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A Spatio-Temporal Deep Learning Model for Automatic Arctic Sea Ice Classification with Sentinel-1 SAR Imagery by Li Zhao, Yufeng Zhou, Wei Zhong, Cheng Jin, Bo Liu, Fangzhao Li

“…Furthermore, to reduce the impact of data imbalance on model performance, the dynamic curriculum learning (DCL) method is used to train the Dynamic MLP model. …”
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Explainable ensemble machine learning revealing spatiotemporal heterogeneity in driving factors of particulate nitro-aromatic compounds in eastern China by M. Li, X. Wang, T. Li, T. Li, Y. Wang, Y. Jiang, Y. Jiang, Y. Zhu, W. Nie, R. Li, J. Gao, L. Xue, Q. Zhang, W. Wang

“…In this work, we combined an ensemble machine learning (EML) model with the SHapley Additive exPlanation (SHAP) and positive matrix factorization (PMF) model to identify the key driving factors for ambient particulate NACs, covering primary emissions, secondary formation, and meteorological conditions based on field observations at urban, rural, and mountain sites in eastern China. …”
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The Effects of Artificial Intelligence Supported Flipped Classroom Applications on Learning Experience, Perception, and Artificial Intelligence Literacy in Higher Education by Mehmet Yavuz, Şener Balat, Bünyami Kayalı

“…It is thought that there is a need for applications based on AI technology that can meet these needs in terms of sustainability of learning, especially in ODE environments where individual learning and instant feedback are important. …”
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The impact of relevant versus irrelevant media multitasking on academic performance during online learning: a serial of mediating models by Lifang Fan, Chen Pan, Xuejun Bai, Shiyi Li, Shiyi Li, Shiyi Li

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