Comparison of the learning outcomes between flipped classroom and interactive lectures among medical undergraduates by Simi Kurian, Manu Mathews, Binoo Divakaran

“…Conclusion: Based on our study, flipped classroom method is having better learning outcome than interactive lectures in terms of post-test scores as well as knowledge retention test scores after 1 month. …”
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The Influence of Flashcard on Arabic Learning Outcomes of Shorof Subject for Junior High School Students by Amy Fitriani Siregar, Ananda Zalfa Firdaus, Agung Setiyawan, Dina Ayu Wulandari, Lutvi Yunita Putri Damayanti, Syifaaussakinah Syifaaussakinah

“…Based on the valid test results, it was suggested that Shorof flashcards can be used in various institutions as Shorof learning subject in general to increase the learning methods more creative and innovative.…”
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Assessing the influence of multimedia instruction on knowledge transfer in higher education: Multimodal learning experiences by Daigo Bernadetha Haule, Thanaa Shaker, Godfrey Yohanes Nkwera

“…Notwithstanding challenges such as curriculum misalignment and resistance to change, the study emphasizes the overwhelmingly positive impact of multimedia on learning outcomes. …”
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External Validation of Persistent Severe Acute Kidney Injury Prediction With Machine Learning Model by Simone Zappalà, PhD, Francesca Alfieri, MS, Andrea Ancona, PhD, Antonio M. Dell’Anna, MD, Kianoush B. Kashani, MD, MS

“…Results from the Amsterdam UMCdb (531 patients, 59 [11.11%] positive) and MIMIC-III (495 patients, 57 [11.52%] positive) cohorts were obtained in a prior development study. …”
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Research on the double-edged sword effect of AI in middle school students’ learning applications by Liu Yuxing

“…This study used a questionnaire survey method to investigate the AI application among 129 students in order to explore the double-edged sword effect of AI in middle school students’ learning. …”
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Precise Crop Pest Detection Based on Co-Ordinate-Attention-Based Feature Pyramid Module by Chenrui Kang, Lin Jiao, Kang Liu, Zhigui Liu, Rujing Wang

“…However, for small-sized crop pests, recent deep-learning-based detection attempts have not accomplished accurate recognition and detection due to the challenges posed by feature extraction and positive and negative sample selection. …”
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Perspectives Regarding Culturally Responsive Teaching in a Mixed-Gender Online Learning Community by Nouf Alsuwaida

“…The study provided positive results for collaborative learning among students of different genders. …”
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Identification of Gingival Inflammation Surface Image Features Using Intraoral Scanning and Deep Learning by Wei Li, Linlin Li, Wenchong Xu, Yuting Guo, Min Xu, Shengyuan Huang, Dong Dai, Chang Lu, Shuai Li, Jiang Lin

“…Conclusion: The study has successfully developed an automatic identification method for surface characteristics of gingival inflammation based on deep learning and IOS technology, providing a standardised and automated auxiliary tool for clinical gingival inflammation examination with high accuracy and significant correlation with clinical indicators. …”
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Learning Intelligent for Effective Sonography (LIFES) Model for Rapid Diagnosis of Heart Failure in Echocardiography by Lies Dina Liastuti, Bambang Budi Siswanto, Renan Sukmawan, Wisnu Jatmiko, Idrus Alwi, Budi Wiweko, Aria Kekalih, Yosilia Nursakina, Rindayu Yusticia Indira Putri, Grafika Jati, Mgs M Luthfi Ramadhan, Ericko Govardi, Aqsha Azhary Nur

“…Background: The accuracy of an artificial intelligence model based on echocardiography video data in the diagnosis of heart failure (HF) called LIFES (Learning Intelligent for Effective Sonography) was investigated. …”
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Deep learning radiopathomics predicts targeted therapy sensitivity in EGFR-mutant lung adenocarcinoma by Taotao Yang, Xianqi Wang, Yuan Jin, Xiaohong Yao, Zhiyuan Sun, Pinzhen Chen, Suyi Zhou, Wentao Zhu, Wei Chen

“…To evaluate its diagnostic performance, we compared the DLRPC model against single-modality models and a decision level fusion model based on Dempster-Shafer theory. Model performances metrics, including area under the curve (AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV), were used for evaluation. …”
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An interpretable deep learning model for the accurate prediction of mean fragmentation size in blasting operations by Baoqian Huan, Xianglong Li, Jianguo Wang, Tao Hu, Zihao Tao

“…The study is based on a database containing 105 samples derived from both previous research and field collection. …”
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Exploring the Controlling Factors of Watershed Streamflow Variability Using Hydrological and Machine Learning Models by Bingbing Ding, Xinxiao Yu, Guodong Jia

“…This study demonstrated the potential of integrating hydrological models with machine learning by constructing two machine learning methods, Extreme Gradient Boosting (XGBoost) and Random Forest (RF), based on the input and output data from the Soil and Water Assessment Tool (SWAT) and comparing their streamflow simulation performances. …”
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Effective Detection of Malicious Uniform Resource Locator (URLs) Using Deep-Learning Techniques by Yirga Yayeh Munaye, Aneas Bekele Workneh, Yenework Belayneh Chekol, Atinkut Molla Mekonen

“…To address these limitations, we propose a deep learning-based approach aimed at developing an effective model for detecting malicious URLs. …”
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A real-time AI tool for hybrid learning recommendation in education: Preliminary results by Chaman Verma

“…This study created an innovative AI tool utilizing the Support Vector Machine (SVM) algorithm on primary samples of Hungarian informatics students to assess their suitability for adopting hybrid learning in their studies. This paper also explained the strength of the model with Shapley Additive exPlanations (SHAP) values of the Explainable Artificial Intelligence (XAI) method. …”
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A Hybrid Deep Learning Model to Accurately Detect Anomalies in Online Social Media by Darbaz M. Hussein, Hakem Beitollahi

“…This paper proposes a hybrid model based on three famous deep learning approaches to discover the behavioral abnormalities, and negative comments in the OSM platforms. …”
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Open-World Semi-Supervised Learning for fMRI Analysis to Diagnose Psychiatric Disease by Chang Hu, Yihong Dong, Shoubo Peng, Yuehan Wu

“…Specifically, we employ spectral augmentation self-supervised learning and dynamic concept contrastive learning to achieve open-world graph learning guided by pseudo-labels, and construct hard positive sample pairs to enhance the network’s focus on potential positive pairs. …”
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SELF-DIRECTED LEARNING SKILLS OF UNDERGRADUATE STUDENTS: A STUDY AT NONG LAM UNIVERSITY - HO CHI MINH CITY, VIETNAM by Nguyen Thi Kim An, Vo Van Viet*

“…The sample of 8472 students was chosen using a convenience sampling method, and data were collected through a structured questionnaire based on the Self-Directed Learning Skills Scale (SDLSS). …”
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Implementation of a hospice community service redesign: Qualitative research identifying lessons learned by Kate Sugar, Candy McCabe, Alison Llewellyn, Wayne de Leeuw, Maggie Crowe, Claire Prendergast, Charlotte Spence, Natasha Bradley

“…Aim: We aimed to capture learning from the implementation experiences of hospice stakeholders during the first 12 months of a hospice community services redesign. …”
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The perception of dental students and educators about e-learning during COVID − 19 pandemic by Shaimaa M. Fouda, Marwa Madi, Passent Ellakany, Nourhan M. Aly, Hala A. Bahgat, Abeer E. Elembaby, Jorma I. Virtanen, Jehan AlHumaid

“…Satisfaction and attitude towards technology-based learning (TBL) were assessed. Two binary logistic regression models were performed to assess the association of factors (age, gender, Grade Point Average, IT skills and experience in TBL) with educators and students’ overall satisfaction and attitude towards TBL. …”
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Optimising test intervals for individuals with type 2 diabetes: A machine learning approach. by Sasja Maria Pedersen, Nicolai Damslund, Trine Kjær, Kim Rose Olsen

“…Model performance is evaluated using ROC-AUC, and optimal intervals are determined based on a "time-to-next-positive-test" concept, with different durations associated with specific intervals.…”
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