Application of artificial intelligence-assisted Traditional Chinese medicine formula granules in bone and joint degenerative diseases in the field of holistic health by Xian-Quan Zhang, Xian-Quan Zhang, Xian-Quan Zhang, Xing-De Wei, Zhuo-Xu Gu, Guang-Hui Zhou, Chu-Jia Huang, Ming-Hui Luo, Ling-Feng Zeng, Ling-Feng Zeng, Ling-Feng Zeng, Wei-Yi Yang, Wei-Yi Yang

“…It analyzes the application models of AI technology in optimizing TCM formula granules, predicting drug efficacy, and personalized treatment. …”
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Relational model of public-private partnership in railway transport by N. F. Sirina, V. P. Pershin

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Analysis of medication rule of Traditional Chinese Medicine in treating depression based on data mining by Jin Yang, Shuai Wang, Zhen Zhang, Junjie Huang, Weihai Chen, Zhan Xu

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Holiday ride-hailing at intercity transfer hubs: Where space squeezes and time stretches by Zhuonan Jiang, Tianqi Gu, Zhuo Chen, Hua Liang, Jiao Jiao, Han Li

“…This study explores the spatiotemporal characteristics of ride-hailing services at intercity transfer hubs in Suzhou, China, examining ride-hailing trip patterns across different land use types, focusing on holidays and regular days. An algorithm is proposed to identify the ride-hailing trips to or from the intercity transfer hubs. …”
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Depression and health literacy among adolescents and adults in Germany: findings from two representative samples by Lars König, Lars König, Rebekka Schröder, Tim Hamer, Ralf Suhr, Ralf Suhr

“…Levels of health literacy (HLS-EU-Q16 questionnaire), depressive symptom severity, rates of depression levels (PHQ-9 questionnaire) and sociodemographic information (age, gender, social status, level of education) were obtained. The associations between sociodemographic factors, health literacy and depression were analyzed using t-tests, analyses of variance and χ2-tests.ResultsOverall, rates of depression were high in both samples (16.5% in adults and 18.4% in adolescents) when measured with the sum score ≥ 10 cut-off criterion and substantially lower when assessed with the diagnostic algorithm criterion (7.2% in adults and 9.8% in adolescents). …”
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Modeling of train flow handling through a limiting single-track section of the route at the organization of high-speed operation using the existing infrastructure by S. V. Karasev, A. D. Kalidova

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Integrated multiomics analysis identifies PHLDA1+ fibroblasts as prognostic biomarkers and mediators of biological functions in pancreatic cancer by Rui Wang, Rui Wang, Guan-Hua Qin, Guan-Hua Qin, Yifei Jiang, Fu-Xiang Chen, Fu-Xiang Chen, Zi-Han Wang, Zi-Han Wang, Lin-Ling Ju, Lin Chen, Da Fu, En-Yu Liu, Su-Qing Zhang, Wei-Hua Cai

“…A 7-gene mCAF-associated risk model was constructed using advanced machine learning algorithms, and the biological significance of PHLDA1 was validated through co-culture experiments and pan-cancer analyses.ResultsOur multiomics analysis revealed that the novel 7-gene model (comprising USP36, KLF5, MT2A, KDM6B, PHLDA1, REL, and DDIT4) accurately predicts patient survival, immunotherapy response, and TME status. …”
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Metabolic profiles in laryngeal cancer defined two distinct molecular subtypes with divergent prognoses by Dan Zheng, Dan Zheng, Xuan Pu, Xuan Pu, XuHui Deng, XuHui Deng, Cui Liu, Cui Liu, SiJun Li, SiJun Li

“…Furthermore, we explored the potentials of several key tumor markers for both diagnosis and prognosis prediction.…”
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Multicenter Development and Prospective Validation of eCARTv5: A Gradient-Boosted Machine-Learning Early Warning Score by Matthew M. Churpek, MD, MPH, PhD, ATSF, Kyle A. Carey, MPH, Ashley Snyder, MPH, Christopher J Winslow, MD, Emily Gilbert, MD, Nirav S Shah, MD, MPH, Brian W. Patterson, MD, MPH, Majid Afshar, MD, MSCR, Alan Weiss, MD, MBA, Devendra N. Amin, MD, Deborah J. Rhodes, MD, Dana P. Edelson, MD, MS

“…All adult patients admitted to the inpatient medical-surgical wards and at 21 hospitals from three health systems for retrospective (2009–2023) and prospective (2023–2024) external validation. PREDICTION MODEL:. Predictor variables (demographics, vital signs, documentation, and laboratory values) were used in a gradient-boosted trees algorithm to predict ICU transfer or death in the next 24 hours. …”
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A capable numerical scheme for solving nonlinear Volterra delay integral equations of the third kind by Rohollah Ghaedi Ghalini, Esmail Hesameddini, Hojatollah Laeli Dastjerdi

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Transdimensional Inference for Gravitational-wave Astronomy with Bilby by Hui Tong, Nir Guttman, Teagan A. Clarke, Paul D. Lasky, Eric Thrane, Ethan Payne, Rowina Nathan, Ben Farr, Maya Fishbach, Gregory Ashton, Valentina Di Marco

“…The tBilby package allows users to set up transdimensional inference calculations using the existing Bilby architecture with off-the-shelf nested samplers and/or Markov Chain Monte Carlo algorithms. Transdimensional models are particularly helpful when seeking to test theoretically uncertain predictions described by phenomenological models. …”
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Development and evaluation of a soft pneumatic muscle for elbow joint rehabilitation by Mostafa Orban, Mostafa Orban, Mostafa Orban, Kai Guo, Kai Guo, Caijun Luo, Caijun Luo, Hongbo Yang, Hongbo Yang, Karim Badr, Karim Badr, Mahmoud Elsamanty, Mahmoud Elsamanty

“…The algorithm achieved a high predictive accuracy of 99.8% in spatial coordination tracking, indicating the precision of the system in monitoring and controlling the actuator’s motion.…”
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GRAVITY ANOMALIES OF THE CRUST AND UPPER MANTLE FOR CENTRAL AND SOUTH ASIA by V. N. Senachin, A. A. Baranov

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Identification of a PANoptosis-related long noncoding rna risk signature for prognosis and immunology in colon adenocarcinoma by Yuekai Cui, Jie Mei, Shengsheng Zhao, Bingzi Zhu, Jianhua Lu, Hongzheng Li, Binglong Bai, Weijian Sun, Wenyu Jin, Xueqiong Zhu, Shangrui Rao, Yongdong Yi

“…Long noncoding RNAs (lncRNAs) play crucial roles in PCD. However, the predictive value of PANoptosis-related lncRNAs (PRlncRNAs) for colon adenocarcinoma (COAD) has not been established. …”
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A validated heart-specific model for splice-disrupting variants in childhood heart disease by Robert Lesurf, Jeroen Breckpot, Jade Bouwmeester, Nour Hanafi, Anjali Jain, Yijing Liang, Tanya Papaz, Jane Lougheed, Tapas Mondal, Mahmoud Alsalehi, Luis Altamirano-Diaz, Erwin Oechslin, Enrique Audain, Gregor Dombrowsky, Alex V. Postma, Odilia I. Woudstra, Berto J. Bouma, Marc-Phillip Hitz, Connie R. Bezzina, Gillian M. Blue, David S. Winlaw, Seema Mital

“…Recent computational algorithms such as SpliceAI have shown an ability to predict such variants, but are not specific to cardiac-expressed genes and transcriptional isoforms. …”
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Constitutive modeling and workability characterization of pre-deformed AZ31 magnesium alloy during hot shear-compression deformation by Junsong Jin, Fangtao Chai, Jinchuan Long, Chang Gao, Shaolei Wang, Pan Zeng, Xuefeng Tang, Pan Gong, Mao Zhang, Lei Deng, Xinyun Wang

“…The developed hot processing map can precisely predict microstructure evolution. The optimal pre-deformation amount is determined to be 2 %, with a recommended hot processing window defined as 300–400 °C and 0.07–7 s−1.…”
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Whole genome sequencing improves tissue-of-origin diagnosis and treatment options for cancer of unknown primary by Richard J. Rebello, Atara Posner, Ruining Dong, Owen W. J. Prall, Tharani Sivakumaran, Camilla B. Mitchell, Aidan Flynn, Alex Caneborg, Catherine Mitchell, Sehrish Kanwal, Clare Fedele, Samantha Webb, Krista Fisher, Hui-Li Wong, Shiva Balachander, Wenying Zhu, Shannon Nicolson, Voula Dimitriadis, Nicholas Wilcken, Anna DeFazio, Bo Gao, Madhu Singh, Ian M. Collins, Christopher Steer, Mark Warren, Narayan Karanth, Huiling Xu, Andrew Fellowes, Rodney J. Hicks, Kym Pham Stewart, Charles Shale, Peter Priestley, Sarah-Jane Dawson, Joseph H. A. Vissers, Stephen B. Fox, Penelope Schofield, David Bowtell, Oliver Hofmann, Sean M. Grimmond, Linda Mileshkin, Richard W. Tothill

“…Curated WGTS features and a CUP prediction algorithm (CUPPA) trained on WGTS data of known cancer types informs TOO in 71% of cases otherwise undiagnosed by clinicopathology review. …”
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Intrusion Detection System Based on Decision Tree and Clustered Continuous Inputs by Adel Issa

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The repertory grids method in the investigation of cognitive differentiation in the sphereof communication by T. G. Siroshtanenko

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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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