Identification and validation of efferocytosis-related biomarkers for the diagnosis of metabolic dysfunction-associated steatohepatitis based on bioinformatics analysis and machine... by Chenghui Cao, Chenghui Cao, Wenwu Liu, Xin Guo, Shuwei Weng, Yang Chen, Yonghong Luo, Shuai Wang, Botao Zhu, Botao Zhu, Yuxuan Liu, Yuxuan Liu, Daoquan Peng

“…To screen for biomarkers for diagnosis, we applied machine learning algorithm to identify hub genes and constructed a clinical predictive model. …”
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Application of deep learning models on single-cell RNA sequencing analysis uncovers novel markers of double negative T cells by Tian Xu, Qin Xu, Ran Lu, David N. Oakland, Song Li, Liwu Li, Christopher M. Reilly, Xin M. Luo

“…Conventional machine learning approaches such as principal component analysis have been employed in single-cell RNA sequencing (scRNA-seq) analysis to characterize DNT cells. …”
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A Digital Mental Health Solution to Improve Social, Emotional, and Learning Skills for Youth: Protocol for an Efficacy and Usability Study by Kayla V Taylor, Laurent Garchitorena, Carolina Scaramutti-Gladfelter, Mykayla Wyrick, Katherine B Grill, Azizi A Seixas

“…Following this, in phase 2, school administrators and teachers undergo intensive training sessions on Neolth’s functionalities and intervention processes as well as understand barriers and facilitators of implementing a digital mental health program at their respective schools. …”
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The impact of relevant versus irrelevant media multitasking on academic performance during online learning: a serial of mediating models by Lifang Fan, Chen Pan, Xuejun Bai, Shiyi Li, Shiyi Li, Shiyi Li

“…BackgroundOnline learning exhibits unique educational benefits, especially in terms of the autonomy, convenience, and flexibility it offers to students. …”
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Deep learning of the particulate and mineral-associated organic carbon fractions using a compositional transform and mid-infrared spectroscopy by Mingxi Zhang, Zefang Shen, Lewis Walden, Farid Sepanta, Zhongkui Luo, Lei Gao, Oscar Serrano, Raphael A. Viscarra Rossel

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Identification and validation of an explainable machine learning model for vascular depression diagnosis in the older adults: a multicenter cohort study by Ran Zhang, Tian Li, Fan Fan, Haoying He, Liuyi Lan, Dong Sun, Zhipeng Xu, Sisi Peng, Jing Cao, Juan Xu, Xiaoxiang Peng, Ming Lei, Hao Song, Junjian Zhang

“…This study aimed to develop and validate an interpretable machine learning (ML) model for VaDep to serve as a clinical support tool. …”
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Feature extraction and classification of digital rock images via pre-trained convolutional neural network and unsupervised machine learning by Masashige Shiga, Masao Sorai, Tetsuya Morishita, Masaatsu Aichi, Naoki Nishiyama, Takashi Fujii

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Identification of Intracranial Germ Cell Tumors Based on Facial Photos: Exploratory Study on the Use of Deep Learning for Software Development by Yanong Li, Yixuan He, Yawei Liu, Bingchen Wang, Bo Li, Xiaoguang Qiu

“…Due to their insidious onset and impact on critical functional areas of the brain, these tumors often result in irreversible abnormalities in growth and development, as well as cognitive and motor impairments in affected children. …”
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Machine learning-based integration of DCE-MRI radiomics for STAT3 expression prediction and survival stratification in breast cancer by Dong Pan, Dong Pan, Dong Pan, Cheng-Yan Zhang, Cheng-Yan Zhang, Cheng-Yan Zhang, Ya-Fei Wang, Ya-Fei Wang, Shuang Liu, Shuang Liu, Shuang Liu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu, Xiong-Zhi Wu

“…A STAT3 predictive model was developed using six machine learning algorithms. Model performance was assessed using receiver operating characteristic (ROC) and related diagnostic statistical indicators.ResultsLow STAT3 expression was significantly associated with poorer OS (hazard ratio [HR] = 1.927, p < 0.001). …”
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Early Attrition Prediction for Web-Based Interpretation Bias Modification to Reduce Anxious Thinking: A Machine Learning Study by Sonia Baee, Jeremy W Eberle, Anna N Baglione, Tyler Spears, Elijah Lewis, Hongning Wang, Daniel H Funk, Bethany Teachman, Laura E Barnes

“…To identify participants at a high risk of dropout, we created 4 unique feature sets: self-reported baseline user characteristics (eg, demographics), self-reported user context and reactions to the program (eg, state affect), self-reported user clinical functioning (eg, mental health symptoms), and passively detected user behavior on the website (eg, time spent on a web page of CBM-I training exercises, time of day during which the exercises were completed, latency of completing the assessments, and type of device used). …”
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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

“…BackgroundAlzheimer's disease (AD) greatly affects the daily functioning and life quality of patients and is prevalent in the elderly population. …”
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Integrating machine learning models with multi-omics analysis to decipher the prognostic significance of mitotic catastrophe heterogeneity in bladder cancer by Haojie Dai, Zijie Yu, You Zhao, Ke Jiang, Zhenyu Hang, Xin Huang, Hongxiang Ma, Li Wang, Zihao Li, Ming Wu, Jun Fan, Weiping Luo, Chao Qin, Weiwen Zhou, Jun Nie

“…In addition, we explored the ceRNA axis containing upstream non-coding RNAs after detailed analysis of pathway activation, immunoregulation, and methylation functions of the core genes. Finally, we performed drug screening and molecular docking experiments based on the core gene in the DSigDB database. …”
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Urban Tree Canopy Mapping and Analysis Using Iterative Annotation Method and Deep Learning: A Case Study in Beijing by Yulong Ding, Ximin Cui, Zhengchao Chen, Zeqing Wang, Debao Yuan, Xiang Meng, Xuan Yang, Yue Xu, Xiangyu Tian

“…Urban trees have significant ecological and social functions, and generating urban tree canopy (UTC) maps is an effective method for understanding their distribution. …”
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T-2 toxin-induced spatial learning and memory impairment in mice via the gut-brain axis and the intervening effects of resveratrol by Sheng-Quan Su, Gui-Yuan Xiong, Chun-Yan Yao, Xiao-Ling Liu, Yin-Yin Xia, Jin-Yun Long, Xiu-Kuan Li, Liang-Mei Wang, Long Yi, Wu-Wei Xu, Wu-Qiang Lu, Qian-Qian Li, Ting Hu, Hao Liu, Ke-Xue Wang, Peng Luo, Tong-Jian Cai

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Understanding the effectiveness and underlying mechanisms of lifestyle modification interventions in adults with learning disabilities: a mixed-methods systematic review by Dikshyanta Rana, Sophie Westrop, Nishant Jaiswal, Evi Germeni, Arlene McGarty, Louisa Ells, Phillippa Lally, Michael McEwan, Craig Melville, Leanne Harris, Olivia Wu

“…Learning disability was defined as a limitation in intellectual functioning (intelligence quotient < 70) and adaptive behaviour with onset before age 18 years. …”
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Transcriptomic signatures of neonatal acute respiratory distress syndrome in a prospective cohort of respiratory distress by Chan Liu, Qing Ai, Jingli Yang, Ying Fan, Wen Jia, Leyu Si, Yuting Yao, Feifan Chen, Shiyue Liu, Yu He, Yuan Shi

“…This study characterized whole blood transcriptomic profiles of NARDS in a pilot cohort of 48 neonates with respiratory distress, demonstrating a significant GA-dependent modulation of gene expression. Functional analyses revealed prominent involvement of interferon-related pathways in NARDS, with greater suppression in neonates born before 34 weeks. …”
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Acute Effects of Low- and High-Speed Resistance Exercise on Cognitive Function in Frail Older Nursing-Home Residents: A Randomized Crossover Study by Hélio J. Coelho-Júnior, Samuel da Silva Aguiar, Riccardo Calvani, Anna Picca, Denise de Azevedo Carvalho, Juliana da Costa Zwarg-Sá, Michel Audiffren, Emanuele Marzetti, Marco Carlos Uchida

“…The present study investigated the acute effects of low- and high-speed resistance exercise on the cognitive function of frail older women living in nursing home. …”
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Extraction of the Optimal Parameters of Single-Diode Photovoltaic Cells Using the Earthworm Optimization Algorithm by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine

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Impact of a 10-week multimodal stress management and lifestyle modification program on stress response and immune function in Crohn’s disease: a mixed-methods approach using the Tr... by Özlem Öznur, Sandra Utz, Christoph Schlee, Jost Langhorst

“…In the qualitative interviews (of the intervention group), patients reported a reduction in stress in their daily lives and in acute stressful situations as a result of using the newly learned specific stress management techniques. The observed improvements in stress management (questionnaire, qualitative interviews), indicated by the reduction in perceived stress, and immune function, suggested by the blood sample results, highlight the potential of integrating multimodal stress management and lifestyle changes into the treatment approach for Crohn’s disease patients. …”
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Evaluation of Brain Function Recovery After Traumatic Brain Injury Treatment in a Porcine Model by Cross-Group Temporal–Spatial Correlation Analysis by Wenwu Sun, William Reeves, Madison M. Fagan, Christina B. Welch, Kelly M. Scheulin, Sydney E. Sneed, Todd R. Callaway, Kylee J. Duberstein, Franklin D. West, Qun Zhao

“…To better understand TBI’s impact on brain function and assess the efficacy of treatments, this study uses a novel temporal–spatial cross-group approach with a porcine model, integrating resting-state functional magnetic resonance imaging (rs-fMRI) for temporal and arterial spin labeling for spatial information. …”
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