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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An examplary application of mathematics teaching based on formative assessment by Aytaç Kurtuluş, Hilal Özcan

“…In this context, it is important to identify and eliminate students’ weaknesses, if any, with the formative assessments in the learning process. The present study aimed to improve the success level of the students with the formative assessment-based teaching practice about circle and circular region in secondary school seventh-grade mathematics teaching and implement an exemplary application for formative assessment-based teaching.Since the study sought to evaluate the learning process of the students and eliminate the weaknesses identified in the process, an action research design, one of the methods of qualitative research, was used. …”
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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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iSKIN: Integrated application of machine learning and Mondrian conformal prediction to detect skin sensitizers in cosmetic raw materials by Weikaixin Kong, Jie Zhu, Peipei Shan, Huiyan Ying, Tongyu Chen, Bowen Zhang, Chao Peng, Zihan Wang, Yifan Wang, Liting Huang, Suzhen Bi, Weining Ma, Zhuo Huang, Sujie Zhu, Xueyan Liu, Chun Li

“…However, with growing concerns over animal ethics and bans on such experiments globally, alternative methods like machine learning are gaining prominence for their efficiency and cost‐effectiveness. …”
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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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Hybrid Deep Learning for Human Fall Detection: A Synergistic Approach Using YOLOv8 and Time-Space Transformers by Yousef Sanjalawe, Salam Fraihat, Mosleh Abualhaj, Salam R. Al-E'Mari, Emran Alzubi

“…To address these issues, we propose a hybrid deep learning-based system that leverages video-based techniques for accurate and efficient fall detection. …”
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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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Enhancing laboratory education through collaborative online international learning: A case study between USA and UK students by Matthew Allan Jones, Pika Miklavc, MaryAnne Stewart

“…This study therefore aims to develop a COIL opportunity that incorporates practical laboratory elements and evaluate the efficacy of this teaching and learning approach.A laboratory-based COIL was developed and delivered across two days. …”
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A Novel Machine Learning Model and a Web Portal for Predicting the Human Skin Sensitization Effects of Chemical Agents by Ricardo Scheufen Tieghi, José Teófilo Moreira-Filho, Holli-Joi Martin, James Wellnitz, Miguel Canamary Otoch, Marielle Rath, Alexander Tropsha, Eugene N. Muratov, Nicole Kleinstreuer

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Ensemble Learning Approaches for Multi-Class Intrusion Detection Systems for the Internet of Vehicles (IoV): A Comprehensive Survey by Manal Alharthi, Faiza Medjek, Djamel Djenouri

“…The NSL-KDD, CICIDS2017, and UNSW-NB15 datasets are widely used to evaluate the performance of Ensemble Learning-Based Intrusion Detection Systems (ELIDS). …”
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Nutritional markers of undiagnosed type 2 diabetes in adults: Findings of a machine learning analysis with external validation and benchmarking. by Kushan De Silva, Siew Lim, Aya Mousa, Helena Teede, Andrew Forbes, Ryan T Demmer, Daniel Jönsson, Joanne Enticott

“…We tested three machine learning algorithms on original and resampled training datasets built using three resampling methods. …”
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SSL-SurvFormer: A Self-Supervised Learning and Continuously Monotonic Transformer Network for Missing Values in Survival Analysis by Quang-Hung Le, Brijesh Patel, Donald Adjeroh, Gianfranco Doretto, Ngan Le

“…The SSL pre-training encompasses two tasks: mask prediction, which identifies positions of absent features, and reconstruction, which endeavors to recover absent elements based on observed ones. …”
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Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus by Lu-Xi Zou, Xue Wang, Zhi-Li Hou, Ling Sun, Jiang-Tao Lu

“…This study aimed to set up DKD risk prediction models based on machine learning algorithms (MLAs) in patients with type 2 DM (T2DM).Methods The electronic health records of 12,190 T2DM patients with 3-year follow-ups were extracted, and the dataset was divided into a training and testing dataset in a 4:1 ratio. …”
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Textual, Genre and Social Features of Spoken Grammar: A Corpus-Based Approach by Carmen Pérez-Llantada

“…This paper describes a corpus-based approach to teaching and learning spoken grammar for English for Academic Purposes with reference to Bhatia’s (2002) multi-perspective model for discourse analysis: a textual perspective, a genre perspective and a social perspective. …”
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Facial Emotion Recognition of 16 Distinct Emotions From Smartphone Videos: Comparative Study of Machine Learning and Human Performance by Marie Keinert, Simon Pistrosch, Adria Mallol-Ragolta, Björn W Schuller, Matthias Berking

“…ObjectiveThis study aimed to develop deep learning–based automatic facial emotion recognition (FER) models for binary (positive vs negative) and multiclass emotion classification tasks, assess the models’ performance, and validate them by comparing the models with human observers. …”
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High-Order Vehicular Pattern Learning and Privacy-Preserving and Unsupervised GAN for Privacy Protection Toward Vehicular Parts Detection by Yanqin Zhang, Zhanling Zhang

“…The model also uses a Gaussian Mixture Model (GMM)-based posterior probability to rank candidate patches for vehicular pattern detection, prioritizing high-risk areas and minimizing false positives. …”
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Students’ motivation, study-effort and perceptions of teachers’ goals when engaging in a learning design within the flipped classroom by Hanne Kristine Skjesol Torbergsen, Tove Engan Paulsby, Gørill Haugan, Britt Karin Utvær

“…The four learning activities are multiple choice questions (MCQ), skills training with Resuscitation Quality Improvement (RQI), team-based learning (TBL) and simulation. …”
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Disentangling shared and unique brain functional changes associated with clinical severity and cognitive phenotypes in schizophrenia via deep learning by Jing Xia, Yi Hao Chan, Deepank Girish, Qian Hui Chew, Kang Sim, Jagath C. Rajapakse

“…Our framework outperforms both single-task and state-of-the-art multi-task learning methods in predicting four Positive and Negative Syndrome Scale (PANSS) subscales and four cognitive domain scores. …”
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T-cell receptor dynamics in digestive system cancers: a multi-layer machine learning approach for tumor diagnosis and staging by Changjin Yuan, Bin Wang, Hong Wang, Fang Wang, Xiangze Li, Ya’nan Zhen

“…Multi-layer machine learning-based diagnostic models were developed by leveraging motif-based feature and deep learning-based feature extraction using ProteinBERT from the 100 most abundant CDR3 sequences per sample. …”
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Enhancing Cyber Security: Comparing the Accuracy of the Bert Model with Other Common Deep Learning Models in Identifying Email Spam by Tao Xu

“…In this study, deep learning (DL) and natural language processing (NLP) methods were employed to develop a spam detection model. …”
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