Low-intensity behavioral activation smartphone app to support low mood: description, engagement and log data analysis by Paul Farrand, Patrick J. Raue, Earlise Ward, Sandra Healey, Jonathan Baker

“…Despite these levels of engagement, however, engagement did not predict changes in scores for either the PHQ-8 [F(2,62) = 2.71; p > 0.05] or GAD-7 [F(2,62) = 0.59; p > 0.05]. …”
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Feasibility of GPT-3.5 versus Machine Learning for Automated Surgical Decision-Making Determination: A Multicenter Study on Suspected Appendicitis by Sebastian Sanduleanu, Koray Ersahin, Johannes Bremm, Narmin Talibova, Tim Damer, Merve Erdogan, Jonathan Kottlors, Lukas Goertz, Christiane Bruns, David Maintz, Nuran Abdullayev

“…Overall agreement between the GPT-3.5 output and the reference standard was assessed by means of inter-observer kappa values as well as accuracy, sensitivity, specificity, and positive and negative predictive values with the “Caret” and “irr” packages. …”
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Transcranial High-Frequency Terahertz Stimulation Alleviates Anxiety-like Behavior in Mice via a Noninvasive Approach by Pan Wang, Chaoyang Tan, Wenyu Peng, Zekun Yan, Wenrui Jiang, Han Zhao, Huaxing Si, Jingchen Jia, Chunkui Zhang, Jian Wang, Yuchen Tian, Kun Chen, Yuefan Yang, Zhenyu Wu, Kangning Xie, Yuanming Wu, Mingming Zhang, Tao Chen

“…Mice were subjected to acute restraint stress to induce anxiety and then clustered into anxiety-susceptible and anxiety-resilient groups using the K-means algorithm. We developed an anxiety phenotype prediction classifier utilizing the naïve Bayes algorithm to accurately categorize mice. …”
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Multicomponent MR Image Denoising by José V. Manjón, Neil A. Thacker, Juan J. Lull, Gracian Garcia-Martí, Luís Martí-Bonmatí, Montserrat Robles

“…In this paper we propose a new filter to reduce random noise in multicomponent MR images by spatially averaging similar pixels using information from all available image components to perform the denoising process. The proposed algorithm also uses a local Principal Component Analysis decomposition as a postprocessing step to remove more noise by using information not only in the spatial domain but also in the intercomponent domain dealing in a higher noise reduction without significantly affecting the original image resolution. …”
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Emergency Department Blood Pressure Management in Type B Aortic Dissection: An Analysis with Machine Learning by Nelson Chen, Jessica V. Downing, Jacob Epstein, Samira Mudd, Angie Chan, Sneha Kuppireddy, Roya Tehrani, Isha Vashee, Emily Hart, Emily Esposito, Rose Chasm, Quincy K. Tran

“…We used random forest (RF) algorithms, a machine-learning tool that uses clusters of decision trees to predict a categorical outcome, to identify predictors of achieving HR and SBP goals prior to ED departure, defined as the time point at which patients left the referring ED to come to our institution. …”
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Integrative analysis of T cell-associated markers in Ewing sarcoma reveals prognostic signatures and immune dynamics by Umair Ali Khan Saddozai, Umair Ali Khan Saddozai, Chenxu Liu, Chenxu Liu, Fei Yan, Zhendong Lu, Muhammad Babar Khawar, Muhammad Babar Khawar, Muhammad Usman Akbar, Saadullah Khattak, Haibo Sun, Haibo Sun, Ping Yang

“…The prognostic model demonstrated high predictive accuracy for 1-, 3-, and 5-year survival (AUC: 0.85, 0.82, 0.78). …”
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Exploring the relationship between sepsis and Golgi apparatus dysfunction: bioinformatics insights and diagnostic marker discovery by Wanli Ma, Xinyi Liu, Ran Yu, Jiannan Song, Lina Hou, Ying Guo, Hongwei Wu, Dandan Feng, Qi Zhou, Haibo Li

“…A diagnostic model constructed using five pivotal genes (B3GNT5, FUT11, MAN1C1, ST6GAL1, and C1GALT1C1) exhibited predictive accuracy, with AUC values exceeding 0.96 for all genes. …”
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Study of the Extended Phase Shift Migration for Three-Dimensional MIMO-SAR Imaging in Terahertz Band by Hang Gao, Chao Li, Shiyou Wu, Hebin Geng, Shen Zheng, Xiaodong Qu, Guangyou Fang

“…Finally, the ‘explode fields’ at time t = 0 can be successfully derived to realize fast imaging reconstruction for MIMO-SAR, with great reduction on the time consuming as compared with the BP algorithm and better accuracy compared with the Stolt migration. …”
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GOES‐R PM2.5 Evaluation and Bias Correction: A Deep Learning Approach by Alqamah Sayeed, Pawan Gupta, Barron Henderson, Shobha Kondragunta, Hai Zhang, Yang Liu

“…Then a DNN based bias correction algorithm is used to improve the accuracies of GOES‐GWR PM2.5. …”
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Reliability and validity of the Transthyretin Amyloidosis – Quality of Life (ATTR-QOL) Questionnaire impact scales by Andrew Lovley, Kristen Hsu, Kaitlin LaGasse, Isabelle Lousada, Kristen L. McCausland, Michelle K. Carty, Sabrina Rebello, Jakob B. Bjorner

“…This study resulted in updates to the ATTR-QOL for item reduction and the development of a scoring algorithm. …”
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Fast Frequency-Domain Compressed Sensing Analysis for High-Density Super-Resolution Imaging Using Orthogonal Matching Pursuit by Saiwen Zhang, Jingjing Wu, Danni Chen, Siwei Li, Bin Yu, Junle Qu

“…Currently, in the spatial domain, the compressive-sensing-based algorithm (CSSTORM) can localize high-emitter-density images. …”
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Exploring the Global and Regional Factors Influencing the Density of <i>Trachurus japonicus</i> in the South China Sea by Mingshuai Sun, Yaquan Li, Zuozhi Chen, Youwei Xu, Yutao Yang, Yan Zhang, Yalan Peng, Haoda Zhou

“…This elucidation of the distinct biological and physical pathways linking these diverse factors leading to <i>T. japonicus</i> density provides a significantly improved foundation for predicting distribution patterns globally and offers concrete scientific insights for sustainable fishery management strategies.…”
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GB-SAR Engineering Interference Suppression Method Integrating Amplitude-Phase Feature Analysis and Robust Regression by Wenting Zhang, Tao Lai, Yuanhui Mo, Haifeng Huang, Qingsong Wang, Zhihua Zhou

“…Experimental results from the Dabao Mountain and Pearl River mining areas demonstrate that the proposed method achieves a reduction of over 80% in the maximum standard deviation of the time-series cumulative phase after suppression, significantly improving phase stability. …”
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Improving Electrical Distance Accuracy for Cable Fault Location Based on the Prony Method by Xiang Ren, Zhiqiang Feng, Kai Zhou, Xueming Zhou, Jianjun Yuan, Yefei Xu, Li Zhang

“…By establishing a frequency-variable coupling model containing the transfer function of the cable with double joint structure, studying the mapping relationship between the cable attenuation constant and the electromagnetic wave velocity, and adopting the Prony estimation method combined with the singular value decomposition noise reduction algorithm to achieve the extraction of the attenuation constant and the decoupling of the segmented wave velocity, thus improving the electrical accuracy of fault location. …”
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Characterization of the salivary microbiome in healthy individuals under fatigue status by Xianhui Peng, Na Han, Yanan Gong, Lihua He, Yanli Xu, Di Xiao, Tingting Zhang, Yujun Qiang, Xiuwen Li, Wen Zhang, Jianzhong Zhang

“…Phenotypic predictions indicated a significant increase in the proportion of bacteria harboring Mobile Genetic Elements (MGEs) (p=0.048), alongside significant reductions in the proportion of aerobic bacteria (p=0.006) and biofilm-forming capacity (p=0.002) in the FTG group. …”
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Identifying the risk of Kawasaki disease based solely on routine blood test features through novel construction of machine learning models by Tzu-Hsien Yang, Ying-Hsien Huang, Yuan-Han Lee, Jie-Nan Lai, Kuang-Den Chen, Mindy Ming-Huey Guo, Yan Pan, Chun-Yu Chen, Wei-Sheng Wu, Ho-Chang Kuo

“…Additional explainable AI analyses revealed that several top predictive features in KDpredictor are consistent with prior clinical findings. …”
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Carbon stock dynamics of forest to oil palm plantation conversion for ecosystem rehabilitation planning by D. Frianto, E. Sutrisno, A. Wahyudi, E. Novriyanti, W.C. Adinugroho, A.S. Yunianto, H. Kurniawan, H. Khotimah, A. Windyoningrum, I.W.S. Dharmawan, H.L. Tata, S. Suharti, H.H. Rachmat, E.M. Lim

“…Data analysis was carried out using Classification and Regression Tree, a decision tree algorithm used in machine learning for guided classification. …”
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Exploring the role of mitochondrial metabolism and immune infiltration in myocardial infarction: novel insights from bioinformatics and experimental validation by Jingyi Hou, Jingyi Hou, Jingyi Hou, Lihan Wang, Lihan Wang, Naiqiang Zhu, Xueli Li

“…A protein-protein interaction (PPI) network of mitoDEGs was constructed, and hub mitoDEGs associated with MI were identified using CytoHubba and molecular complex detection (MCODE) algorithms. Transcription factor (TF) and microRNA (miRNA) targets of hub mitoDEGs were predicted using iRegulon and miRWalk plug-ins, respectively, and a regulatory network involving TFs, hub mitoDEGs, and miRNA was established. …”
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Interaction between the assembly of the ribosomal subunits: Disruption of 40S ribosomal assembly causes accumulation of extra-ribosomal 60S ribosomal protein uL18/L5. by Nusrat Rahman, Md Shamsuzzaman, Lasse Lindahl

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Experimental investigation and optimization of epoxy composites reinforced with jute fiber and alumina using the Jaya ANFIS approach by Lakshmi Narayana Somsole, P. Thejasree, K. L. Narasimhamu, Manikandan Natarajan, G. Velmurugan, Dinesh Ramesh Salunke, Vinod P. Sakhare, Pramod Kumar, Regasa Yadeta Sembeta

“…Abstract Composites reinforced with natural fibers are increasingly progressively in diverse engineering practices for their remarkable attributes, including weight reduction, high strength, cost-efficiency, biodegradability, and renewability. …”
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