Multiple Tumor-related autoantibodies test enhances CT-based deep learning performance in diagnosing lung cancer with diameters < 70 mm: a prospective study in China by Qingcheng Meng, Pengfei Ren, Lanwei Guo, Pengrui Gao, Tong Liu, Wenda Chen, Wentao Liu, Hui Peng, Mengjia Fang, Shuo Meng, Hong Ge, Meng Li, Xuejun Chen

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Prediction of new HIV infection in men who have sex with men based on machine learning: secondary analysis of a prospective cohort study from Western China by Kangjie Li, Guiqian Shi, Cong Zhang, Bing Lin, Yi Tao, Qian Wang, Haijiao Zeng, Jielian Deng, Lei Zou, Biao Xie, Xiaoni Zhong

“…Objective This study aimed to construct a model based on machine learning to predict new HIV infections in HIV-negative men who have sex with men (MSM).Methods This is a secondary analysis of a previous random clinical trial aiming to evaluate the preventive effects of PrEP on new HIV infection in MSM. …”
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Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

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Using AR to Enhance the Learning of Chirality by Martin Bullock, Johannes Huwer

“…An initial pilot study involving 11th-grade students revealed positive student attitudes towards AR, with participants reporting enhanced comprehension of chirality and a preference for AR-based learning over traditional methods. …”
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Advanced intelligent techniques for modeling oxygen storage in zeolite-based porous materials by Arefeh Naghizadeh, Ahmadreza Jafari-Sirizi, Behnam Amiri-Ramsheh, Saeid Atashrouz, Dragutin Nedeljkovic, Ahmad Mohaddespour, Abdolhossein Hemmati-Sarapardeh

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Graph-based analysis of histopathological images for lung cancer classification using GLCM features and enhanced graph by Imam Dad, JianFeng He, Zulqarnain Baloch

“…This paper introduces a novel Enhanced GraphSAGE (E-GraphSAGE) framework that integrates graph-based deep learning (GBDL) with traditional image processing to classify lung cancer subtypes—Adenocarcinoma (ACA), Squamous Cell Carcinoma (SCC), and Benign Tissue (BNT)—from H&amp;E-stained Whole-Slide Images (WSIs). …”
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The Research Trends and the Effectiveness of Smart Learning by Ilkyu Ha, Chonggun Kim

“…In this study, research documents about smart learning from 2007 have been treated based on 5 major searching sites; we investigate the research trends of smart learning of education. …”
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Does digital learning stimulate creativity? by Marcel Pikhart, Liqaa Habeb Al-Obaydi, Blanka Klimova

“…The findings indicate that digital learning generally can have a certain but positive impact on creativity. …”
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A hybrid Hadoop-based sentiment analysis classifier for tweets associated with COVID-19 utilizing two machine learning algorithms: CNN, and fuzzy C4.5 by Fatima Es-sabery, Ibrahim Es-sabery, Junaid Qadir, Beatriz Sainz-de-Abajo, Begonya Garcia-Zapirain

“…Implemented on a Hadoop framework-based cluster with five computing units, the approach was extensively tested. …”
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Who excels in online learning in Japan? by Eisuke Tokiwa

“…The correlation calculations were based on Equations 1-3, which provide the framework for assessing relationships between variables.ResultsThe analysis revealed that conscientiousness had the strongest positive influence on learning outcomes, with students scoring high in conscientiousness achieving superior results, particularly in STEM subjects. …”
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Enhancing cold storage efficiency: Continuous deep deterministic policy gradient approach to energy optimization utilizing strategic sensor input data by Jong-Whi Park, Young-Min Ju, Hak-Sung Kim

“…The proposed algorithm represents a significant advancement in the field of energy management for cold storage, combining real-time data-driven learning with robust control strategies. Therefore, Experimental results demonstrate a remarkable 19.8 % reduction in energy consumption compared to conventional methods while maintaining a stable target temperature of −10 °C. …”
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The Impact of Teaching Strategies in Blended Learning on Students’ Self-Directed Learning Capability at Hanoi University of Science and Technology by Viet Anh Mai, Chi Quynh Nguyen, Ngoc Thang Duong, Mai Quynh Thi Tran, Hoc Hieu Le

“…The teaching strategies that have the most positive impact on SDL are Active Learning, Problem-Based Learning, and Personalized Learning. …”
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A Visibility-Based Historical PM2.5 Estimation for Four Decades (1981–2022) Using Machine Learning in Thailand: Trends, Meteorological Normalization, and Influencing Factors Using... by Nishit Aman, Sirima Panyametheekul, Ittipol Pawarmart, Sumridh Sudhibrabha, Kasemsan Manomaiphiboon

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Simulated Practice Learning Experience in a Virtual Environment: An Innovative Pedagogical Approach to Practice Learning for Nursing Students by Sharon Faulds, Anne Taylor

“…There is a wealth of evidence to support the positive impact simulated learning or simulated-based education can have on the student experience, developing skill competency and enhancing patient outcomes. …”
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Inclusive Storytelling: Immigrant Experiences and Community Reaction in Georgia by Darlene Xiomara Rodriguez, Paul N. McDaniel, Lina Tuschling, Lara Smith-Sitton

“…This paper examines how community-based service-learning initiatives create new visions for civic engagement and what research methods help us ascertain community impact and opinion. …”
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Evaluating Virtual Game Design for Cultural Heritage Interpretation: An Exploratory Study on arkeOyun by Sevde Güner, Leman Figen Gül

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The association of obesity and lipid-related indicators with all-cause and cardiovascular mortality risks in patients with diabetes or prediabetes: a cross-sectional study based on... by Zhaoqi Yan, Xing Chang, Zhiming Liu, Ruxiu Liu, Xiufan Du

“…Additionally, we compared the predictive performance of eight machine learning (ML) algorithms regarding mortality risk and used the SHAP method to clarify the significance of obesity and lipid-related indicators in mortality prediction.ResultsThe results of the multivariable Cox regression analysis reveal significant associations between TyG, TyG-WWI, and ABSI with all-cause mortality among patients with diabetes/prediabetes. …”
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Developing an Explainable Artificial Intelligence System for the Mobile-Based Diagnosis of Febrile Diseases Using Random Forest, LIME, and GPT by Kingsley F. Attai, Constance Amannah, Moses Ekpenyong, Daniel E. Asuquo, Oryina K. Akputu, Okure U. Obot, Peterben C. Ajuga, Jeremiah C. Obi, Omosivie Maduka, Christie Akwaowo, Faith-Michael Uzoka

“…Methods We integrated the interpretability offered by local interpretable model-agnostic explanations (LIME) and the explainability provided by generative pre-trained transformers (GPT) to bridge the gap in understanding and trust often created by machine learning models in critical healthcare decision-making. …”
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Improving UAV-Based Detection of Low-Emission Smoke with an Advanced Dataset Generation Pipeline by Marek Szczepański

“…To overcome this, we refine an existing motion-based annotation framework by integrating an LightGBM-based classifier, which filters out false positives caused by background motion. …”
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Deep Learning for the Early Diagnosis of Candidemia by Daniele Roberto Giacobbe, Sabrina Guastavino, Anna Razzetta, Cristina Marelli, Sara Mora, Chiara Russo, Giorgia Brucci, Alessandro Limongelli, Antonio Vena, Malgorzata Mikulska, Alessio Signori, Antonio Di Biagio, Anna Marchese, Ylenia Murgia, Marco Muccio, Nicola Rosso, Michele Piana, Mauro Giacomini, Cristina Campi, Matteo Bassetti

“…Both feature selection and transfer learning did not improve the diagnostic performance of a model based on BDG and PCT only. …”
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