Machine learning cluster analysis identifies increased 12-month mortality risk in transcatheter aortic valve replacement recipients by Thomas Meredith, Thomas Meredith, Thomas Meredith, Farhan Mohammed, Amy Pomeroy, Sebastiano Barbieri, Sebastiano Barbieri, Erik Meijering, Louisa Jorm, David Roy, Jason Kovacic, Jason Kovacic, Jason Kovacic, Jason Kovacic, Michael Feneley, Michael Feneley, Michael Feneley, Christopher Hayward, Christopher Hayward, Christopher Hayward, David Muller, David Muller, David Muller, Mayooran Namasivayam, Mayooran Namasivayam, Mayooran Namasivayam

“…Unsupervised machine learning permits pattern discovery within complex multidimensional patient data and may facilitate recognition of groups requiring closer post-TAVR surveillance.MethodsWe analysed and differentiated routinely collected demographic, biochemical, and cardiac imaging data into distinct clusters using unsupervised machine learning. k-means clustering was performed on data from 200 patients who underwent TAVR for severe aortic stenosis (AS). …”
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Can machine learning distinguish between elite and non-elite rowers? by Orten Kristine Fjellkårstad, Helgesen Sander Elias Magnussen, Chen Bihui, Baselizadeh Adel, Torresen Jim, Herrebrøden Henrik

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Exploring trends and emerging topics in oceanography (1992–2021) using deep learning-based topic modeling and cluster analysis by Mingyu Han, Yuntao Zhou

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How Much is Character Education Correlated with Learning Outcomes of Islamic Religious Education Students in Indonesia: Meta-Analysis Study by Astuti Rahayu Fuji, Susanti Eka, Yusnaldi Eka, Budiman, Arsyad Junaidi, Setyawan Agung

“…A meta-correlation analysis was employed, analyzing data from 36 independent studies derived from 24 primary sources published between 2019 and 2023. …”
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Use the 4S (Signal-Safe Speckle Subtraction): Explainable Machine Learning Reveals the Giant Exoplanet AF Lep b in High-contrast Imaging Data from 2011 by Markus J. Bonse, Timothy D. Gebhard, Felix A. Dannert, Olivier Absil, Faustine Cantalloube, Valentin Christiaens, Gabriele Cugno, Emily O. Garvin, Jean Hayoz, Markus Kasper, Elisabeth Matthews, Bernhard Schölkopf, Sascha P. Quanz

“…In the present work, we use explainable machine learning to investigate the reason for the loss of the planet signal for one of the most used postprocessing methods: principal component analysis (PCA). …”
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Progress on the world’s primate hotspots and coldspots: modeling ensemble super SDMs in cloud-computers based on digital citizen-science big data and 200+ predictors for more susta... by Moriz Steiner, Falk Huettmann

“…For this analysis, all occurrences have been merged into one multi-species (400+ species) pixel-based analysis. …”
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ANALYSIS IMPLEMENTATION OF TECHNOLOGICAL PEDAGOGICAL CONTENT KNOWLEDGE BY SCIENCE TEACHERS THROUGH DISTANCE LEARNING AT JUNIOR HIGH SCHOOL IN MEDAN by Rizky Agassy Sihombing, Grace Angeline Manurung, Lia Angraini Simanjuntak

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Deep learning enhanced road traffic analysis: Scalable vehicle detection and velocity estimation using PlanetScope imagery by Maciej Adamiak, Yulia Grinblat, Julian Psotta, Nir Fulman, Himshikhar Mazumdar, Shiyu Tang, Alexander Zipf

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A Deep Learning based Hybrid Model for Maternal Health Risk Detection and Multifaceted Emotion Analysis in Social Networks by Geethanjali R., Valarmathi A.

“…In the field of public health, accurately identifying maternal health risks through social network data is both vital and challenging due to the complexities of multimodal sentiment analysis. …”
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Remote sensing-driven machine learning models for spatiotemporal analysis of coastal phytoplankton blooms under climate change scenarios by Siqi Wang, Shuzhe Huang, Yinguo Qiu, Xiang Zhang, Chao Wang, Nengcheng Chen

“…We evaluated multiple machine learning approaches including Logistic Regression (LR), Linear Discriminant Analysis (LDA), Classification and Regression Tree (CART), Extreme Gradient Boosting (XGboost), and Light Gradient Boosting Machine (LightGBM) for their predictive capabilities. …”
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Predictive analysis of clinical features for HPV status in oropharynx squamous cell carcinoma: A machine learning approach with explainability by Emily Diaz Badilla, Ignasi Cos, Claudio Sampieri, Berta Alegre, Isabel Vilaseca, Simone Balocco, Petia Radeva

“…Conclusions:: The combination of specific clinical factors typically collected for OPSCC patients, such as smoking habits and the tumor oropharynx sub-location, along with the ML models hereby presented, can by themselves provide an informed analysis of the HPV status, and of proper use of data science techniques to explain it. …”
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Analysis of Science Learning Outcomes on Matter and Its Changes in Seventh-Grade MTs Students Reviewed from Gender Differences by Fatimah Az-Zahro, Dian Nugraheni, Aisyah Az-Zahro, Isnanik Juni Fitriyah, Yayuk Mulyati, Erti Hamimi

“… This study investigates science learning outcomes on the topic Matter and Its Changes among seventh-grade students at MTs, with a focus on gender differences. …”
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Predicting honest behavior based on Eysenck personality traits and gender: an explainable machine learning study using SHAP analysis by Yu Meng, Zili Peng, Zhitong Zhang, Qiaolin Chen, Hanxi Huang, Yihan Chen, Mengqian Zhao

“…SHAP analysis revealed: (1) neuroticism as the strongest predictor of dishonesty; (2) significant gender differences (higher dishonesty rates in males); and (3) threshold effects for Psychoticism and Extraversion.DiscussionThis work makes three key contributions: (1) first systematic application of the Eysenck model to aviation honesty prediction; (2) identification of gender as a critical moderating variable; and (3) development of a SHAP-driven interpretable framework that connects machine learning outputs with psychological theory. …”
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A Scalable Framework for Real-Time Network Security Traffic Analysis and Attack Detection Using Machine and Deep Learning by Zineb Maasaoui, Mheni Merzouki, Abdella Battou, Ahmed Lbath

“…Our Network Security Traffic Analysis Platform employs a comprehensive technology stack including the Elastic Stack, ZEEK, Osquery, Kafka, and GeoLocation data. …”
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Driver Injury Prediction and Factor Analysis in Passenger Vehicle-to-Passenger Vehicle Collision Accidents Using Explainable Machine Learning by Peng Liu, Weiwei Zhang, Xuncheng Wu, Wenfeng Guo, Wangpengfei Yu

“…SHAP analysis was utilized to interpret the model and conduct a comprehensive analysis of accident features, including their importance, dependencies, and combined effects on severity prediction. …”
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Accelerated Bayesian optimization for CNN+LSTM learning rate tuning via precomputed Gaussian process subspaces in soil analysis by Xiaolong Chen, Hongfeng Zhang, Cora Un In Wong, Zhengchun Song

“…PurposeWe propose an accelerated Bayesian optimization framework for tuning the learning rate of CNN+LSTM models in soil analysis, addressing the computational inefficiency of traditional Gaussian Process (GP)-based methods. …”
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Exploring the potential of machine learning and magnetic resonance imaging in early stroke diagnosis: a bibliometric analysis (2004–2023) by Jian-cheng Lou, Xiao-fen Yu, Jian-jun Ying, Da-qiao Song, Wen-hua Xiong

“…This investigation covered the period from 2004 to 2023, with the data retrieval completed on December 1, 2023, in a single day.ResultsIn total, 395 articles were incorporated into the analysis. …”
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A Comparative Analysis of Buckling Pressure Prediction in Composite Cylindrical Shells Under External Loads Using Machine Learning by Hyung Gi Lee, Jung Min Sohn

“…This study addressed this challenge by integrating advanced machine learning techniques with simulation-based data generation through finite element analysis (FEA). …”
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Social media interaction and built environment effects on urban walking experience: A machine learning analysis of Shanghai Citywalk. by Xingrui Chen, Yu Sun, Filzani Illia Binti Ibrahim, Myzatul Aishah Binti Kamarazaly, Siti Norzaini Binti Zainal Abidin, Suqiu Tang

“…From the perspective of virtual-physical interaction, this study integrates social media data with geospatial information, utilizing machine learning methods and spatial statistical analysis to explore the multidimensional driving mechanisms and complex relationships affecting the emotional experiences of Citywalk participants. …”
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Lessons learned in transition: a bibliometric analysis of educational management in school transfer to provincial administrative organizations during decentralization by Jiraporn Chano, Bahtiar Mohamad, Denchai Prabjandee, Rungthip Singporn, Melinda Tuaypar

“…Using a dataset of 190 publications and authors’ keyword co-occurrence data, the study examines trends, patterns, and knowledge gaps from 2018 to 2024. …”
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