Racial disparities in diabetes care and outcomes for people with visual impairment: a descriptive analysis of the TriNetX research network by Charisse Madlock-Brown, Austin Lee, Jaime Seltzer, Anthony Solomonides, Nisha Mathews, Jimmy Phuong, Nicole Weiskopf, William G. Adams, Harold Lehmann, Juan Espinoza

“…Abstract Background This research delves into the confluence of racial disparities and health inequities among individuals with disabilities, with a focus on those contending with both diabetes and visual impairment. Methods Utilizing data from the TriNetX Research Network, which includes electronic medical records of roughly 115 million patients from 83 anonymous healthcare organizations, this study employs a directed acyclic graph (DAG) to pinpoint confounders and augment interpretation. …”
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Bayesian model parameter learning in linear inverse problems: application in EEG focal source imaging by Alexandra Koulouri, Ville Rimpiläinen

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Preoperative prediction of pulmonary ground-glass nodule infiltration status by CT-based radiomics combined with neural networks by Kun Mei, Zikang Feng, Hui Liu, Min Wang, Chao Ce, Shi Yin, Xiaoying Zhang, Bin Wang

“…The neural network architecture combined a 3D convolutional neural network (CNN) with random rotations for data augmentation and employed pre-trained parameters to optimize model weights. …”
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Nairobi Early Childcare in Slums (NECS) Study Protocol: a mixed-methods exploration of paid early childcare in Mukuru slum, Nairobi by Sunil Bhopal, Zelee Hill, Elizabeth W Kimani-Murage, Robert C Hughes, Patricia Kitsao-Wekulo, Betty R Kirkwood

“…Quantitative and spatial data will be analysed through epidemiological methods (random effects regression modelling and spatial statistics).Ethics and dissemination Ethical approval has been granted in the UK and Kenya. …”
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Intrusion Detection and Mitigation Method for the Industrial Internet of Things Using Bidirectional Convolutional Long Short-Term Memory and Deep Recurrent Convolutional Q-Networks by Zhang Yan, Piyush Kumar Shukla, Prashant Kumar Shukla, Kanika Thakur, Anurag Sinha, Saifullah Khalid

“…ADASYN data augmentation is used to address class imbalance, while entropy analysis and statistical techniques are used to extract key features. …”
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A Method for Custom-Contoured Cushion Fabrication Based on Pressure Mapping for Wheelchair Users to Prevent Pressure Ulcers: Feasibility Quasi-Experimental Study by Alma De León-Hernández, Adriana Martínez-Hernández, Isabel Bolivar-Tellería, Andrea Bosch-Sánchez, María Fernanda Cabrera-Padilla, Carlos Omar López-López

“…In the second phase, 10 cushions for wheelchair users were manufactured and tested. The resulting data from buttock pressure using a flat foam, Jay ResultsIn the validation study, the statistically significant difference between the flat and the custom-contoured cushion showed a better performance in pressure relief for the custom cushion (mean pressure 27.3, SD 4.5 mm Hg and 34.6, SD 3.5 mm Hg; PP2PP ConclusionsThe main finding is that the buttock pressure mapping method produces custom-contoured cushions that, compared with commercial cushions, have good pressure distribution and increased contact area. …”
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A Novel Approach to Generate a Virtual Population of Human Coronary Arteries for <italic>In Silico</italic> Clinical Trials of Stent Design by Dimitrios Pleouras, Antonis Sakellarios, George Rigas, Georgia S. Karanasiou, Panagiota Tsompou, Gianna Karanasiou, Vassiliki Kigka, Savvas Kyriakidis, Vasileios Pezoulas, George Gois, Nikolaos Tachos, Aidonis Ramos, Gualtiero Pelosi, Silvia Rocchiccioli, Lampros Michalis, Dimitrios I. Fotiadis

“…<italic>Methods:</italic> A clinical data augmentation algorithm is implemented to efficiently generate virtual clinical data using a real clinical dataset. …”
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An Attention-based Model for Recognition of Facial Expressions Using CNN-BiLSTM by Sushil Kumar Singh, Manish Kumar, Ikram Majeed Khan, A. Jayanthiladevi, Chirag Agarwal

“…The results demonstrate that our proposed model outperforms existing approaches, highlighting the effectiveness of incorporating attention paradigms, hybrid deep learning architectures, and advanced preprocessing methods for facial emotion detection. The non-parametric statistical test also analyzes it.…”
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Comparing the Effect of Beractant (Beraksurf™) with That of Poractant Alfa (Curosurf®) on the Need for Intermittent Positive Pressure Ventilation in Neonatal Respiratory Distress S... by Yosra Khazani, Sirous Fathi Manesh, Elnaz Shaseb, Parvin Sarbakhsh

“…This study aimed to estimate the effect of beractant (Beraksurf™, Tekzima Company), compared with the Poractant alfa (Curosurf®, Chiesi Pharmaceuticals), as surfactant replacement therapy, on the need for Intermittent Positive Pressure Ventilation (IPPV) in Neonatal Respiratory Distress Syndrome (NRDS) more precisely by fitting a semi-parametric efficient model adjusted for appropriate covariates. Method This study is secondary and we re-analyzing data of a published RCT. …”
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Enhancing Hierarchical Classification in Tree-Based Models Using Level-Wise Entropy Adjustment by Olga Narushynska, Anastasiya Doroshenko, Vasyl Teslyuk, Volodymyr Antoniv, Maksym Arzubov

“…Future research will focus on integrating neural networks with hierarchy-aware metrics, enhancing data augmentation to address class imbalance, and developing real-time classification systems for practical use in industries such as retail, logistics, and healthcare.…”
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Empirical Re-Investigation into the Export-Led Growth Hypothesis (ELGH): Evidence from EAC and SADC Economies by Ojo Johnson Adelakun, Oluwafemi Opeyemi Ojo, Sakhile Mpungose

“…The analysis covers 22 EAC and SADC economies from 1990 to 2022—regions marked by structural transformation efforts, trade liberalisation, and participation in the AfCFTA. A dynamic panel data model based on an augmented Cobb-Douglas production function is estimated using the System Generalised Method of Moments (System GMM) to address endogeneity and reverse causality. …”
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Component Analysis When Testing for Fixed Effects in Unbalanced ANOVAs by J. C. W. Rayner, G. C. Livingston

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Review of Synthetic Aperture Radar Automatic Target Recognition: A Dual Perspective on Classical and Deep Learning Techniques by Jakub Slesinski, Damian Wierzbicki

“…The performance has further been enhanced with techniques, such as transfer learning, unsupervised learning, and adversarial learning, to overcome data scarcity and variability. Alongside these techniques, this review also looks at application-specific methods suited to operational needs, such as real-time detection, robust classification, an identification of small objects, and new data handling techniques, such as data augmentation and multimodal fusion. …”
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Expectation-maximization alternating least squares for tensor network logistic regression by Naoya Yamauchi, Hidekata Hontani, Tatsuya Yokota, Tatsuya Yokota

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Task-aware conditional GAN with multi-objective loss for realistic and efficient industrial time series generation by Kai Lang, Yonghua Li

“…To address these challenges, we propose a novel conditional generative adversarial framework that integrates statistical feature augmentation, multi-scale temporal windows, and a composite loss function combining adversarial, L2, DTW, FID, and statistical constraints. …”
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Space-scale exploration of the poor reliability of deep learning models: the case of the remote sensing of rooftop photovoltaic systems by Gabriel Kasmi, Laurent Dubus, Yves-Marie Saint-Drenan, Philippe Blanc

“…Finally, based on our analysis, we introduce a data augmentation technique designed to improve the robustness of deep learning classifiers under varying acquisition conditions. …”
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Robust lung segmentation in Chest X-ray images using modified U-Net with deeper network and residual blocks by Wiley Tam, Paul Babyn, Javad Alirezaie

“…An ablation study was conducted to evaluate these architectural components, along with additional elements like augmented data, alternative backbones, and attention mechanisms. …”
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Self‐Supervised Classification of Weather Systems Based on Spatiotemporal Contrastive Learning by Liwen Wang, Qian Li, Qi Lv

“…However, the existing classification methods are challenged due to a lack of labels and inaccurate similarity measures between data samples. …”
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Divergent confidence intervals among pre-specified analyses in the HiSTORIC stepped wedge trial: An exploratory post-hoc investigation. by Richard A Parker, Catriona Keerie, Christopher J Weir, Atul Anand, Nicholas L Mills

“…In particular, the observed divergence between the calendar-matched and other analyses remained, even after performing the covariate adjustment methods, and after using data augmentation. Divergence was particularly acute for the safety endpoint, which had an event rate of 0.36% overall. …”
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Role of Artificial Intelligence and Deep Learning in Easier Skin Cancer Detection through Antioxidants Present in Food by Sreevidya R. C., Jalaja G, Sajitha N, D. Lakshmi Padmaja, S. Nagaprasad, Kumud Pant, Yekula Prasanna Kumar

“…“Deep Learning” (DL) is an effective method to detect cancerous lesions. The study’s purpose is to comprehend the vital function performed by DL methods in supporting healthcare professionals in easier skin cancer detection using big data networks. …”
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