Machine Learning-Based Obesity Classification: A Comparative Study Using Self-Reported Survey Data and Ensemble Learning Models by Gregorius Airlangga

“…This study explores the use of machine learning for obesity classification based on self-reported survey data collected from individuals in Mexico, Peru, and Colombia. …”
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The relationship between nurse contact time and patient outcomes: a retrospective observational study using Real-Time Location data by Elena Ashtari Tafti, Ann-Marie Cannaby, Vanda Carter, Stephenson Strobel

“…While previous research has demonstrated that higher nurse staffing levels lead to better outcomes, the specific contribution of increased direct patient care time to these improvements remains unknown. Using data from a Real-Time Location System (RTLS) that tracks the movement of staff and patients across the hospital wards using Global Positioning System (GPS) sensors, we can estimate the time patients “actually” spend with nursing staff during an inpatient stay. …”
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Integrating metro passenger flow data to improve the classification of urban functional regions using a heterogeneous graph neural network by Pengxin Zhang, Min Yang, Yong Wang, Taiyang Yang, Huafei Yu, Xiongfeng Yan

“…Initially, we constructed a heterogeneous graph with blocks and metro stations as nodes, connected based on their spatial proximity and crowd flow interactions. Subsequently, the building morphological and POI categorical features and crowd mobility features were used as the descriptive features of the block and metro station nodes, respectively. …”
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Exploration of the Formation Mechanism of Underground Brine Based on Hydrodynamic Environment Analysis Using Grain-Size Data of One Drilling Core by Qiao Su, Ying Yu, Mingjun Chen, Tengfei Fu, Wenzhe Lyu, Wenquan Liu

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Quantification of droplet and contact transmission risks among elementary school students based on network analyses using video-recorded data. by Shuta Kikuchi, Keisuke Nakajima, Yasuki Kato, Takeshi Takizawa, Junichi Sugiyama, Taisei Mukai, Yasushi Kakizawa, Setsuya Kurahashi

“…Therefore, in this study, actual behavioral data were collected using video recordings to evaluate droplet and contact transmission in elementary schools. …”
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SHEIB-AGM: A Novel Stochastic Approach for Detecting High-Order Epistatic Interactions Using Bioinformation With Automatic Gene Matrix in Genome-Wide Association Studies by Liyan Sun, Guixia Liu, Rongquan Wang

“…Detecting epistatic interactions in GWAS (genome-wide association studies) data is of great significance in studying common and complex diseases; however, the ability to detect high-order epistatic interactions in GWAS data is still insufficient. …”
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Geospatial Robust Wheat Yield Prediction Using Machine Learning and Integrated Crop Growth Model and Time-Series Satellite Data by Rana Ahmad Faraz Ishaq, Guanhua Zhou, Guifei Jing, Syed Roshaan Ali Shah, Aamir Ali, Muhammad Imran, Hongzhi Jiang, Obaid-ur-Rehman

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Developing a robust yield prediction model for potatoes (Solanum tuberosum L.) using multi-faceted and multi-year data by Alfadhl Y. Alkhaled, Yi Wang

“…It developed random forest (RF) models to predict final tuber yield using different model inputs, including genotype (G) (cultivar), management (M) practices (N treatment), environmental (E) factors (soil temperature and precipitation), and hyperspectral data that was obtained by smart agriculture technologies (T). …”
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Measuring the effects of community polygyny on intimate partner violence: a multilevel modeling using nationally representative cross-sectional data by Zacharie Tsala Dimbuene, Bright Opoku Ahinkorah, Dickson Abanimi Amugsi

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Audit reporting standards data from experimental marketsMendeley Data by Eric Gooden, Mark Mellon

“…Moreover, the data can be used to provide additional empirical evidence to regulators on the efficacy of both identity disclosure and signature requirements on audit reporting quality.…”
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Diagnosis of winter precipitation types using the spectral bin model (version 1DSBM-19M): comparison of five methods using ICE-POP 2018 field experiment data by W. Bang, J. T. Carlin, K. Kim, A. V. Ryzhkov, A. V. Ryzhkov, G. Liu, G. Lee

“…Three reference WPTs (snow (SN), rain (RA), and RASN) are obtained from particle size velocity (PARSIVEL) disdrometer data using a newly proposed decision tree algorithm. …”
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A Rapid Adaptation Approach for Dynamic Air-Writing Recognition Using Wearable Wristbands with Self-Supervised Contrastive Learning by Yunjian Guo, Kunpeng Li, Wei Yue, Nam-Young Kim, Yang Li, Guozhen Shen, Jong-Chul Lee

“…The model can learn prior features from unlabeled signals of random wrist movements, significantly reducing the dependency on extensive labeled data for training. The wristband system rapidly adapts to multiple scenarios after fine-tuning using few-shot data, enhancing user interaction through natural and intuitive communication.…”
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Optimizing soybean variety selection for the Pan-African Trial network using factor analytic models and envirotyping by Maurício S. Araújo, João P. S. Pavan, André A. Stella, Bruno F. Fregonezi, Natally F. Lima, Erica P. Leles, Michelle F. Santos, Peter Goldsmith, Godfree Chigeza, Brian W. Diers, José B. Pinheiro

“…This study aimed to identify soybean varieties with high overall performance and stability using multi-environment trial data from the Pan-African Soybean Trial Network. …”
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It’s Time to Relax: The Critical Importance of Digital Mental Health Products in the Context of Surveillance Capitalism by Sena Partal, Sasha Smirnova

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Selective agreement, not sycophancy: investigating opinion dynamics in LLM interactions by Erica Cau, Valentina Pansanella, Dino Pedreschi, Giulio Rossetti

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Accurate prediction of synergistic drug combination using a multi-source information fusion framework by Shuting Jin, Huaze Long, Anqi Huang, Jianming Wang, Xuan Yu, Zhiwei Xu, Junlin Xu

“…Specifically, we design a semi-supervised learning framework using an attributed graph neural network to integrate protein–protein interaction networks of gene expression products with multi-omics data, constructing initial cell line representations that incorporate multi-source information. …”
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Synthetic Patient–Physician Conversations Simulated by Large Language Models: A Multi-Dimensional Evaluation by Syed Ali Haider, Srinivasagam Prabha, Cesar Abraham Gomez-Cabello, Sahar Borna, Ariana Genovese, Maissa Trabilsy, Bernardo G. Collaco, Nadia G. Wood, Sanjay Bagaria, Cui Tao, Antonio Jorge Forte

“…Background: Data accessibility remains a significant barrier in healthcare AI due to privacy constraints and logistical challenges. …”
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USE OF PERAMPANEL IN THE TREATMENT OF EPILEPSY: A REVIEW OF LITERATURE AND A CASE REPORT by K. Yu. Mukhin, O. A. Pylaeva

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Innovative Approach to Detecting Autism Spectrum Disorder Using Explainable Features and Smart Web Application by Mohammad Abu Tareq Rony, Fatama Tuz Johora, Nisrean Thalji, Ali Raza, Norma Latif Fitriyani, Muhammad Syafrudin, Seung Won Lee

“…Autism Spectrum Disorder (ASD) is a complex developmental condition marked by challenges in social interaction, communication, and behavior, often involving restricted interests and repetitive actions. …”
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Strategic Planning for Sustainable Urban Park Vitality: Spatiotemporal Typologies and Land Use Implications in Hangzhou’s Gongshu District via Multi-Source Big Data by Ge Lou, Qiuxiao Chen, Weifeng Chen

“…This study constructs a “temporal behavior–spatial attributes–park typology” framework using high-precision (50 m) mobile signaling data to capture hourly vitality fluctuations in 59 parks of Hangzhou’s Gongshu District. …”
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