Explainable Deep Multilevel Attention Learning for Predicting Protein Carbonylation Sites by Jian Zhang, Jingjing Qian, Pei Wang, Xuan Liu, Fuhao Zhang, Haiting Chai, Quan Zou

“…These innovative designs have been shown to successfully boost predictive performance and statistically outperforms current methods. Particularly, results on benchmark testing dataset demonstrate that SCANS consistently achieves low false positive rates, including low rates of cross‐predictions. …”
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The Role of Immersive Virtual Realities: Enhancing Science Learning in Higher Education by Talia Tene, Marco Guevara, Gabriel Moreano, John Vera, Cristian Vacacela Gomez

“…Particularly, 18 articles demonstrated a significant positive or increased impact on learning outcomes. …”
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Knee Osteoarthritis Detection and Classification Using Autoencoders and Extreme Learning Machines by Jarrar Amjad, Muhammad Zaheer Sajid, Ammar Amjad, Muhammad Fareed Hamid, Ayman Youssef, Muhammad Irfan Sharif

“…Methods: The proposed model differentiates between KOA-positive and KOA-negative images and categorizes the disease into its primary severity levels. …”
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DeSPPNet: A Multiscale Deep Learning Model for Cardiac Segmentation by Elizar Elizar, Rusdha Muharar, Mohd Asyraf Zulkifley

“…Methods: This paper proposes DeSPPNet, a multiscale-based deep learning network. …”
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Caplaire Learning Model: An Effective Strategy to Improve Science Literacy Skills by Lala Ananda

“…Findings indicate a significant improvement in students' scientific literacy following the implementation of the Caplaire model, with higher post-test scores and positive feedback from students and lecturers. The Caplaire model, which integrates inquiry-based learning and reflection, effectively engaged students and fostered a deeper understanding of scientific concepts. …”
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Transforming molecular diagnostics learning: the power of gamification in higher medical education by Hua Zhu, Wei Zeng, Li Chen

“…Participants engaged in a four-unit “Gene Detective” game, solving clinical cases through molecular techniques, earning skill points, and collaborative inquiry learning in group discussions.ResultsData from skill assessments, self-reported competency scales, final exam scores from the concurrent course, and post-course questionnaires revealed significant improvements in core competencies especially in critical thinking, curiosity, creativity and communication skill, with a positive correlation between game-based skill values and academic performance. …”
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Grammar learning in a flipped classroom: Measuring achievement and students’ perceptions by Haile Abrha Gebregziabher, Abiy Yigzaw Filate, Kassie Shifere Bishaw

“…However, no correlation was found between the two variables. Based on these findings, the study concluded that flipped learning positively impacted grammar achievement and was well-perceived by the students. …”
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Adaptive Dynamic Programming with Reinforcement Learning on Optimization of Flight Departure Scheduling by Hong Liu, Song Li, Fang Sun, Wei Fan, Wai-Hung Ip, Kai-Leung Yung

“…Moreover, perturbation simulations of ADP parameters validate the method’s robustness and efficacy. ADP, when integrated with reinforcement learning, demonstrates time efficiency and reliability, positioning it as a viable solution for decision-making in departure management systems.…”
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Using machine learning to predict the rupture risk of multiple intracranial aneurysms by Junqiang Feng, Chunyi Wang, Yu Wang, He Liu, He Liu

“…ObjectiveThis study aims to develop a machine learning-based risk prediction model (RPM) for the rupture of multiple intracranial aneurysms (MIAs), addressing a critical gap in current clinical tools such as the PHASES score, which are not specifically designed for MIAs. …”
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Deep Learning Multi-Modal Melanoma Detection: Algorithm Development and Validation by Nithika Vivek, Karthik Ramesh

“…ObjectiveThis study aimed to present a novel multimodal deep learning-based technique to distinguish between melanoma and seborrheic keratosis. …”
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Predicting mortgage credit defaults in morocco using machine learning approaches by Amine Hade, Mohamed Elhia

“…From a simple model using logistic regression to modern and advanced models based on ensemble methods, ten different models were explored. …”
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Undergraduate Nursing Students' Satisfaction of The Clinical Learning Environment in Iraq-Kurdistan by Zuhair Rushdi Mustafa, Safiya Sabri Piro

“…Objectives: This study aims to assess the level of undergraduate nursing students' satisfaction toward their clinical learning in Duhok City. Material and Methods: A cross-sectional descriptive study design used. …”
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Rethinking Domain‐Specific Pretraining by Supervised or Self‐Supervised Learning for Chest Radiograph Classification: A Comparative Study Against ImageNet Counterparts in Cold‐Star... by Han Yuan, Mingcheng Zhu, Rui Yang, Han Liu, Irene Li, Chuan Hong

“…We also identified promising outcomes related to cold‐start AL, including initialization based on pretrained models, the positive influence of initialization on subsequent learning, the potential for one‐shot initialization, and the influence of class balance on middle‐budget AL. …”
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An interactive mobile three-dimensional virtual laboratory for learning ear anatomy by Atina Putri, Fahma Waluya Rosmansyah, Chessa Nur Triejunita, Yuda Sukmana, Nyilo Purnami, Sakina Sakina, Yuni Sari Amalia, Yusep Rosmansyah

“…A cross-over repeated measures design was conducted to compare students’ experiences with both types of learning methods: conventional and VLab. To analyze students’ perceptions of VLab, a five-point Likert scale comprising 22 question items was utilized based on the hedonic-motivation system adoption model, which includes seven variables: heightened enjoyment, behavioral intention to use, perceived usefulness, curiosity, control, perceived ease of use, and focused immersion (FI). …”
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The use of a workbook as an efficient didactic means of teaching Russian in secondary vocational education organizations by L. M. Gareeva, A. V. Malkina, T. V. Mandzhieva

“…The purpose of the study is to confirm the effectiveness and expediency of a workbook use as a didactic tool for self-development of educational material within the framework of applying competence-based and activity-based approaches to learning.Materials and methods. …”
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Enhancing automatic early arteriosclerosis prediction: an explainable machine learning evidence by Eka Miranda, Suko Adiarto

“…Objective: This paper proposed a machine learning (ML) model to early predict patients with arteriosclerotic heart disease (AHD). …”
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Live Weight Prediction in Norduz Sheep Using Machine Learning Algorithms by Cihan Çakmakçı

“…There were no differences between the means of actual and predicted LWs by machine learning models. The fact that the models generalized well on the testing data sets indicates that machine learning algorithms have valid predictive patterns and are effective methods in LW weight of Norduz sheep. …”
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DIDACTIC POTENTIAL OF MOBILE APPLICATIONS FOR LEARNING ENGLISH AS A FOREIGN LANGUAGE by Blynova Neliia, Kyrylova Oksana, Dolzhenko Maryna

“…Research methods: the analysis of sources on the topic of research made it possible to understand the state of development of the topic, the main directions of domestic and foreign research on mobile learning; descriptive provided an opportunity to generalize the experience gained during reconnaissance; synthesis of the obtained data contributed to the conclusion of the research concept and its implementation. …”
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Intelligent Stroke Disease Prediction Model Using Deep Learning Approaches by Chunhua Gao, Hui Wang

“…Finally, the proposed method is compared with commonly used machine learning-based classification algorithms such as decision tree, random forest, support vector machine, and artificial neural networks. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

“…In this study, we applied machine learning to routine programme data from Kenya's EMR to predict the probability that an individual seeking care is undiagnosed HIV positive and should be prioritized for testing. …”
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