MoveMentor—examining the effectiveness of a machine learning and app-based digital assistant to increase physical activity in adults: protocol for a randomised controlled trial by Corneel Vandelanotte, Stewart Trost, Danya Hodgetts, Tasadduq Imam, MD Mamunur Rashid, Quyen G. To, Carol Maher

“…Intervention participants will gain access to an app-based physical activity digital assistant that can learn and adapt in real-time to achieve high levels of personalisation and user engagement by virtue of applying a range of machine learning techniques (i.e. reinforcement learning, natural language processing and large language models). …”
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Longitudinal Analysis of Risk Factors for Pulmonary Function Decline in Chronic Lung Diseases Over Five Years by Li L, Meng J, Chen J

“…Both calibration and decision curves further substantiated the reliability of the model in identifying patients at increased risk for pulmonary function decline.Conclusion: The predictive model developed in this study serves as a valuable tool for clinicians to target early interventions and optimize treatment strategies to enhance the quality of care and patient outcomes in the management of CLDs.Keywords: chronic lung diseases, pulmonary function decline, latent class growth modeling, random forest model, health services, machine learning in healthcare…”
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Towards the implementation of automated scoring in international large-scale assessments: Scalability and quality control by Ji Yoon Jung, Lillian Tyack, Matthias von Davier

“…This study addresses this challenge by investigating two machine learning approaches — supervised and unsupervised learning — for scoring multilingual responses. …”
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Penerapan Model Algoritma Unsupervised Learning untuk Klasterisasi Tingkat Kenyamanan Ruang Tidur berdasarkan Faktor Lingkungan by Mhd Idham Khalif, Listyo Edi Prabowo

“…Abstract In the era of Industry 4.0, technologies such as cloud computing, robotics, the Internet of Things (IoT), artificial intelligence (AI), and machine learning (ML) have been extensively developed across various sectors, including industry, government, education, and even households. …”
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Efficient Explainable Models for Alzheimer’s Disease Classification with Feature Selection and Data Balancing Approach Using Ensemble Learning by Yogita Dubey, Aditya Bhongade, Prachi Palsodkar, Punit Fulzele

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Deep learning-based recognition model of football player’s technical action behavior using PCA–LBP algorithm by Hongtao Chen, Zhengbai Lin, Quan Xu

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The Role of Artificial Intelligence in Sports Analytics: A Systematic Review and Meta-Analysis of Performance Trends by Przemysław Pietraszewski, Artur Terbalyan, Robert Roczniok, Adam Maszczyk, Kajetan Ornowski, Daria Manilewska, Szymon Kuliś, Adam Zając, Artur Gołaś

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Predicting New York Heart Association (NYHA) heart failure classification from medical student notes following simulated patient encounters by Ishan R. Perera, Taylor Daniels, Janella Looney, Kimberly Gittings, Frederic A. Rawlins

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Deep reinforcement learning Lane-Change Decision-Making for autonomous vehicles based on motion primitives library in hierarchical action space by Guizhe Jin, Zhuoren Li, Bo Leng, Minhua Shao

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Impact of Urban Expansion on School Quality in Compulsory Education: A Spatio-Temporal Study of Dalian, China by Zhenchao Zhang, Weixin Luan, Chuang Tian, Min Su

“…This study integrates a random forest machine learning model, GIS spatial analysis, and a spatial econometric model to examine the spatiotemporal differentiation of school quality in Dalian, China, in 2016 and 2020, as well as its relationships with the construction land development cycle, population density, and housing prices. …”
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A hybrid approach using support vector machine rule-based system: detecting cyber threats in internet of things by M. Wasim Abbas Ashraf, Arvind R. Singh, A. Pandian, Rajkumar Singh Rathore, Mohit Bajaj, Ievgen Zaitsev

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Local or Neighborhood? Examining the Relationship between Traffic Accidents and Land Use Using a Gradient Boosting Machine Learning Method: The Case of Suzhou Industrial Park, Chin... by Yueming Yang, Hyungchul Chung, Joon Sik Kim

“…Using a case study of Suzhou Industrial Park (SIP) in Suzhou, China, this paper examines the relationship between different land use types and traffic accidents using a gradient boosting model (GBM) machine learning method. The results show that the GBM can be used as an effective accident model for a variety of research and analysis methods by (1) ranking the influential factors, (2) testing the degree of interpretation of each variable as the complexity of iterations changes, and (3) obtaining partial dependence plots, among other methods. …”
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Colorectal cancer detection with enhanced precision using a hybrid supervised and unsupervised learning approach by Akella S. Narasimha Raju, K. Venkatesh, Ranjith Kumar Gatla, Eswara Prasad Konakalla, Marwa M. Eid, Nataliia Titova, Sherif S. M. Ghoneim, Ramy N. R. Ghaly

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A novel deep learning-based spider wasp optimization approach for enhancing brain tumor detection and physical therapy prediction by Suleiman Daoud, Ahmad Nasayreh, Khalid M.O. Nahar, Wlla k. Abedalaziz, Salem M. Alayasreh, Hasan Gharaibeh, Ayah Bashkami, Amer Jaradat, Sultan Jarrar, Hammam Al-Hawamdeh, Absalom E. Ezugwu, Raed Abu Zitar, Aseel Smerat, Vaclav Snasel, Laith Abualigah

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Machine learning-derived prognostic signature integrating programmed cell death and mitochondrial function in renal clear cell carcinoma: identification of PIF1 as a novel target by Guangyang Cheng, Zhaokai Zhou, Shiqi Li, Fu Peng, Shuai Yang, Chuanchuan Ren

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Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

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Annotated emotional image datasets of Chinese university students in real classrooms for deep learningMendeley Data by Chengliang Wang, Haoming Wang, Zihui Hu, Xiaojiao Chen

“…This dataset provides a reliable foundation for future research and applications in educational technology, particularly in the development of real-time emotion recognition models to enhance personalized learning and teaching effectiveness. …”
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Detecting Transit Deserts Through a Blend of Machine Learning (ML) Approaches, Including Decision Trees (DTs), Logistic Regression (LR), and Random Forest (RF) in Lucknow by Alok Tiwari

“…As urban populations expand, addressing transit accessibility requires advanced data-driven approaches. This study applies machine learning (ML) models, decision trees (DTs), logistic regression (LR), and random forest (RF), within an Intelligent Transport System (ITS) framework to detect transit deserts in Lucknow, India. …”
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Secure IoMT for Disease Prediction Empowered With Transfer Learning in Healthcare 5.0, the Concept and Case Study by Tahir Abbas Khan, Areej Fatima, Tariq Shahzad, Atta-Ur-Rahman, Khalid Alissa, Taher M. Ghazal, Mahmoud M. Al-Sakhnini, Sagheer Abbas, Muhammad Adnan Khan, Arfan Ahmed

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A multi-filter deep transfer learning framework for image-based autism spectrum disorder detection by Rodrigo Colnago Contreras, Monique Simplicio Viana, Victor José Souza Bernardino, Francisco Lledo dos Santos, Önsen Toygar, Rodrigo Capobianco Guido

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