Prevalence, Clinical Features, and Associated Factors of Atrial Fibrillation Among Hypertensive Patients at Fort Portal Regional Referral Hospital, Uganda by Jama YM, Jayte M, Hersi AM, Muhammad P, Peris A, Saed AI, Hussein M, Hussein A, Abdi AA, Nur IA, Mohamud MH

“…Variables with p < 0.2, odds ratios ≥ 2 or ≤ 0.5, or biological plausibility were included in the multivariable model. Significance was set at p < 0.05. Data analysis was performed using Stata version 15.2.Findings: Among 140 hypertensive patients, the prevalence of AF was 10% (n = 14). …”
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Anti-crisis activities and export performance in the Covid-19 pandemic: The case of Polish exporters by Nelly Daszkiewicz, Aleksandra Kordalska, Magdalena Olczyk

“…To verify the assumed relationships, we used the probit regression model. Findings: We found that some firm key features, such as firm size, the territorial scope of international activity, the share of foreign ownership in assets, the degree of innovation, and the presence of a market diversification strategy significantly impacted export sales during the pandemic. …”
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Ultrasound derived deep learning features for predicting axillary lymph node metastasis in breast cancer using graph convolutional networks in a multicenter study by Enock Adjei Agyekum, Wentao Kong, Doris Nti Agyekum, Eliasu Issaka, Xian Wang, Yong-zhen Ren, Gongxun Tan, Xuan Jiang, Xiangjun Shen, Xiaoqin Qian

“…In validation cohort 1, the US-based GCN model performed satisfactorily, with an AUC of 0.88 and an accuracy of 0.76. …”
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Simulation Study of the Air Separation Performance of Cr-MIL-101 in High-Altitude Environments by Ying-Chao Wang, Yuan-Zhe Li, Ming-Ming Zhai, Cheng-Cheng Zhao, Kang-Ning Xie, Er-Ping Luo, Chi Tang, Chen-Xu Zhang

“…The conclusion of this study provides theoretical support for optimizing the N2/O2 separation performance of Cr-MIL-101 in high-altitude environments.…”
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MAE‐SigNet: An effective network for automatic modulation recognition by Shilong Zhang, Yu Song, Shubin Wang

“…However, existing deep learning‐based AMR methods often need to consider the sensitivity of models to noise fully. This study proposes a masked autoencoder multi‐scale attention feature fusion model (MAE‐SigNet). …”
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Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning by Jiayuan Xu, Andrew J. Doig, Sofia Michopoulou, Sofia Michopoulou, Petroula Proitsi, Petroula Proitsi, Fumie Costen, The Alzheimer's disease neuroimaging initiative

“…We conducted a feature matching technique to enable our model to be tested on the external dataset without retraining.ResultsOur system achieved a value of 0.95 for the Area Under the ROC curve (AUC) using the ADNI dataset (n = 340) and the full set of 11 features. …”
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The influence of performance expectancy, hedonic motivation, and effort expectancy on mobile augmented reality habits by Prabhavathy R, S. Senthilkumar, Paul Arun Kumar J, K. Subathra, Ajith L, Wang Yuyang, Rohan Thomas Jinu

“…This model states that Mobile Augmented Reality habits influence Millennials’ performance expectancy, hedonic motivation, and effort expectancy. …”
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Boosting Barlow Twins Reduced Order Modeling for Machine Learning‐Based Surrogate Models in Multiphase Flow Problems by T. Kadeethum, V. L. S. Silva, P. Salinas, C. C. Pain, H. Yoon

“…To evaluate the performance of BBT‐ROM, we conduct three three‐dimensional multiphase flow problems, including waterflooding and geologic carbon storage (GCS), with varying numbers of input parameter cases and model domain features. …”
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Experimental and numerical investigations of microthermal actuator employing the amplification theory for achieving competitive performance by Mohamed Abdelsalam Mansour, Mustafa M. Elsayed, Alaa M. Ali, Abdelrahman Toraya, Noha Gaber

“…Therefore, the comparison with other designs has included all the main specifications that are of concern. The performance is discussed based on the main features of any thermal actuator: displacement, temperature, area, and applied voltage, all combined in a performance evaluation index (PEI). …”
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Photocatalytic Performances of Dip-Coated Ag Doped TiO2 Thin Films by M. Alharbi, H. Althubyani, E. Alarfaj, D. Dastan, A. Timoumi, L. Tao, H. Albetran, Ş. Ţălu

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CFNet: Optimizing Remote Sensing Change Detection Through Content-Aware Enhancement by Fan Wu, Sijun Dong, Xiaoliang Meng

“…CFNet employs EfficientNet-B5 as the backbone for feature extraction. To enhance the model’s focus on the content features of images while mitigating the misleading effects of style features, we develop a constraint strategy that prioritizes the content features of bitemporal images, termed Content-Aware. …”
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Interpretability-Oriented Adjustment of K-Means: A Multiple-Objective Particle Swarm Optimization Framework by Liang Chen, Leming Sun, Caiming Zhong

“…To address this, this paper proposes a feature selection model to balance the interpretability and clustering quality. …”
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A framework for predictive modeling of microbiome multi-omics data: latent interacting variable-effects (LIVE) modeling by Javier Munoz Briones, Douglas K. Brubaker

“…Here, we present a framework for integration of microbiome multi-omics data: Latent Interacting Variable Effects (LIVE) modeling. LIVE integrates multi-omics data using single-omic latent variables (LV) organized in a structured meta-model to determine the combinations of features most predictive of a phenotype or condition. …”
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Efficient high performance computing with the ALICE event processing nodes GPU-based farm by Federico Ronchetti, Federico Ronchetti, Valentina Akishina, Valentina Akishina, Edvard Andreassen, Nora Bluhme, Nora Bluhme, Gautam Dange, Gautam Dange, Jan de Cuveland, Jan de Cuveland, Giada Erba, Hari Gaur, Hari Gaur, Dirk Hutter, Dirk Hutter, Grigory Kozlov, Grigory Kozlov, Luboš Krčál, Sarah La Pointe, Sarah La Pointe, Johannes Lehrbach, Johannes Lehrbach, Volker Lindenstruth, Volker Lindenstruth, Volker Lindenstruth, Gvozden Nešković, Gvozden Nešković, Andreas Redelbach, Andreas Redelbach, David Rohr, Felix Weiglhofer, Felix Weiglhofer, Alexander Wilhelmi, Alexander Wilhelmi

“…Due to the increase of data volumes expected for the LHC Run 3 and Run 4, the ALICE Collaboration designed and deployed a new, energy efficient, computing model to run Online and Offline O2 data processing within a single software framework. …”
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SARFA-Net: Shape-Aware Label Assignment and Refined Feature Alignment for Arbitrary-Oriented Object Detection in Remote Sensing Images by Yan Dong, Minghong Wei, Guangshuai Gao, Chunlei Li, Zhoufeng Liu

“…Numerous excellent detection models perform promising results, however, there are two main tough challenges hinder their performances. …”
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Construction and validation of prognostic model for ICU mortality in cardiac arrest patients: an interpretable machine learning modeling approach by Yong Li, Ying Liu, Qing Zhang, Hongwei Zhu, Chengli Wen, Xian Jiang

“…The model with the largest area under the Receiver Operating Characteristic (ROC) curve (AUC) and good performance in other features was defined as the best model, and Shapley Additive Explanations (SHAP) was used to improve the interpretability of the optimal model. …”
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The value of 18F-FDG PET/CT combined with 3D quantitative technology and clinicopathological features in predicting prognosis of NSCLC by Yuling Su, Siwen Qiu, Jinyu Wang

“…Cox proportional hazards regression was used to develop models based on clinicopathological features to predict prognosis of NSCLC patients. …”
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Polymorphism of the second type angiotensin II receptor’s gene in women with essential hypertension and the corresponding features of structural and functional parameters of myocar... by O. O. Sakovych, V. M. Zhebel, T. V. Polishchuk, S. V. Franchuk, L. M. Sursaieva

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SENTIMENT ANALYSIS OF REVIEWS ON X APPS ON GOOGLE PLAY STORE USING SUPPORT VECTOR MACHINE AND N-GRAM FEATURE SELECTION by Fahri Aimar Kusumo, Dewi Retno Sari Saputro, Purnami Widyaningsih

“…This research aims to perform sentiment analysis on  application reviews on the Google Play Store with SVM and unigram, bigram, and trigram feature selection. …”
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Research on the Influence of Axle Deviation Angle on Riding Performance of Autonomous-Rail Rapid Trams by YU Juan, ZHOU Sheng, PENG Jing, LIU Xiaocong

“…Based on vehicle dynamics modeling, the study investigated the impact of axle deviation on vehicle riding performance, through lateral dynamics analysis and calculations. …”
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