Ar-Enhanced Reading Instruction: Impact on Indonesian EFL Learners' Comprehension and Attitudes by Mustakim Sagita, Issy Yuliasri, Abdurrahman Faridi, Hendi Pratama

“…Employing a quasi-experimental mixed-method design, 62 university students were divided into an experimental group (n=31) and a control group (n=31). …”
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Statistical analysis plan for the ARtificially Intelligent image fusion system versus standard treatment to guide endovascular Aortic aneurysm repair (ARIA): a multi-centre randomi... by Hatem A. Wafa, James Budge, Tom Carrell, Medeah Yaqub, Matt Waltham, Izabela Pilecka, Joanna Kelly, Caroline Murphy, Stephen Palmer, Rachel E. Clough, Yanzhong Wang

“…The statistical analysis plan outlines methods for handling missing data, covariates for adjusted analyses, and planned sensitivity analyses to ensure robust evaluation of treatment effects. …”
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Reliability-enhanced data cleaning in biomedical machine learning using inductive conformal prediction. by Xianghao Zhan, Qinmei Xu, Yuanning Zheng, Guangming Lu, Olivier Gevaert

“…Accurately labeling large datasets is important for biomedical machine learning yet challenging while modern data augmentation methods may generate noise in the training data, which may deteriorate machine learning model performance. …”
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Lightweight anomaly detection model for UAV networks based on memory-enhanced autoencoders by HU Tianzhu, SHEN Yulong, REN Baoquan, HE Ji, LIU Chengliang, LI Hongjun

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Machine learning detection of Gaussian steering in continuous-variable systems under data imbalance by Jie Guo, Taotao Yan, Jinchuan Hou, Xiaofei Qi, Kan He

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Win Ratio in Biomedical Science: A Bibliometric Analysis by Zhenyu Li, MSc, Aliya Izumi, HBSc, Dominique Vervoort, MD, MPH, CPH, MBA, Anika Ranadive, HBSc, Subodh Verma, MD, Stephen E. Fremes, MD, MSc

“…Background: The win ratio (WR), introduced in 2012, has emerged as a method to analyze hierarchical composite outcomes by prioritizing clinically significant events, unlike traditional composite time-to-event analyses, which treat events equally. …”
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Boosting EEG and ECG Classification with Synthetic Biophysical Data Generated via Generative Adversarial Networks by Archana Venugopal, Diego Resende Faria

“…Techniques such as discrete wavelet transform, downsampling, and upsampling were employed to enhance data quality. This method shows significant potential in addressing biophysical data scarcity and advancing applications in assistive technologies, human-robot interaction, and mental health monitoring, among other medical applications.…”
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Adoption of Data-Driven Automation Techniques to Create Smart Key Performance Indicators for Business Optimization by Michael Sishi, Arnesh Telukdarie

“…To address this issue, this paper proposes a method that combines statistics, machine learning (ML), and artificial intelligence (AI) to augment traditional KPIs with the flexibility of data-driven automation (DDA) techniques. …”
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Tratamento da ptose mamária e hipomastia utilizando técnica de mamoplastia com pedículo súpero-medial e implante mamário Treatment of breast ptosis and hypomastia using the superom... by Alexandre Wada, Lincoln Saito Millan, Samuel Terra Gallafrio, Rolf Gemperli, Marcus Castro Ferreira

“…METHODS: The incidence of complications and surgical revision was analyzed in 27 patients who underwent one-stage mastopexy combined with breast augmentation using the superomedial pedicle technique, between 2005 and 2010. …”
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Large language models generating synthetic clinical datasets: a feasibility and comparative analysis with real-world perioperative data by Austin A. Barr, Joshua Quan, Eddie Guo, Emre Sezgin, Emre Sezgin

“…Recent advances in large language models (LLMs) provide an opportunity to generate synthetic data with reduced reliance on domain expertise, computational resources, and pre-training.ObjectiveThis study aims to assess the feasibility of generating realistic tabular clinical data with OpenAI’s GPT-4o using zero-shot prompting, and evaluate the fidelity of LLM-generated data by comparing its statistical properties to the Vital Signs DataBase (VitalDB), a real-world open-source perioperative dataset.MethodsIn Phase 1, GPT-4o was prompted to generate a dataset with qualitative descriptions of 13 clinical parameters. …”
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A holistic framework for intradialytic hypotension prediction using generative adversarial networks-based data balancing by Hsuan-Ming Lin, JrJung Lyu

“…Traditional oversampling methods often struggle with complex clinical data. …”
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Avaliação da qualidade de cicatrizes em mamoplastia de aumento por via submamária e transareolomamilar: um estudo longitudinal prospectivo Scar quality evaluation following transar... by Denis Souto Valente, Lauro Aita Carvalho, Marcelo Tonding Ferreira

“…METHODS: A prospective study investigated patients who underwent aesthetic breast augmentation. …”
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Targeted lipidomics dataset of central nervous system and plasma from mice with experimental autoimmune encephalomyelitisMendeley Data by Jörn Lötsch, Irmgard Tegder, Natasja de Bruin, Dominique Thomas, Gerd Geisslinger

“…Standardized variable naming and detailed metadata facilitate cross-referencing and integration with other datasets.This resource enables comparative analyses of lipid profiles across tissues and treatment groups. It supports statistical and machine learning applications and enables the evaluation of data augmentation strategies, including statistical and generative AI approaches. …”
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Motor neuron disease: The impact of decreased speech intelligibility on marital communication by K. Joubert, J. Bornman

“…Communication is one of the most constructive ways of dealing with emotions that are elicited by these changes. Method: This study explored the association between the deteriorating speech of persons with MND and couples’ perception of marital communication. …”
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Simulation Study to Identify Factors Affecting the Performance of LSTM and XGBoost for Anomaly Detection on Labeled Time Series Data by Muhammad Rizky Nurhambali, Yenni Angraini, Anwar Fitrianto

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Spatial Cluster Detection Under Dependent Random Environmental Effects by Walguen Oscar, Jean Vaillant

“…Overdispersion and spatial dependence must be taken into account in the modeling, otherwise the classical scan statistics method may lead to the detection of false clusters. …”
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Four-parameter beta mixed models with survey and sentinel 2A satellite data for predicting paddy productivity by Dian Kusumaningrum, Hari Wijayanto, Anang Kurnia, Khairil Anwar Notodiputro, Muhlis Ardiansyah, Islam MD Parvez

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Towards Context-Rich Automated Biodiversity Assessments: Deriving AI-Powered Insights from Camera Trap Data by Paul Fergus, Carl Chalmers, Naomi Matthews, Stuart Nixon, André Burger, Oliver Hartley, Chris Sutherland, Xavier Lambin, Steven Longmore, Serge Wich

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Quantifying model output uncertainty from sparse input data: a case study in the Mississippi sound and mobile bay by Meena Raju, Anna Linhoss, Raúl J. Osorio

“…Statistical measures of performance were used to: (1) compare interpolated inputs across methods, (2) assess model outputs based on each interpolation method, and (3) compare modeled outputs with observed data. …”
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Adjustment for sparse data bias in odds ratios: Significance to appraisal of risk of diabetes due to occupational trichlorfon insecticide exposure by Igor Burstyn, David Miller

“…Next, we applied easily accessible methods that adjust for sparse data bias to the extracted contingency tables, including data augmentation, bootstrap, Firth's regression, and Bayesian methods with weakly informative priors. …”
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