Improved estimation of two-phase capillary pressure with nuclear magnetic resonance measurements via machine learning by Oriyomi Raheem, Misael M. Morales, Wen Pan, Carlos Torres-Verdín

“…To approach the common condition of sparsely sampled training data, we transformed the prediction problem into an overdetermined one by applying composite fitting to both capillary pressure and pore throat size distribution, and Gaussian cumulative distribution fitting to the NMR T2 measurements, generating evenly sampled data points. …”
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Radiomic Analysis of Contrast‐Enhanced CT Predicts Recompensation in Hepatitis B‐Related Decompensated Cirrhosis by Qiaofeng Chen, Yuanping Fan, Kaini Wu, Tianpan Cai, Chunyu Lan, Mingju Yu, Yunfeng Fu, Qi Zhu, Jianhao Qiu, Xiaodong Zhou

“…Three machine‐learning algorithms were used to develop radiomic signatures. …”
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TEMPORALITY OF THE NARRATIVE OF CONTEMPORARY TRAVEL LITERATURE (Based on Cees Nooteboom’s work) by Olena I. Kretova, Pavlo V. Kretov

“…In the case of travel literature, the temporality of the narrative algorithmizes and structures the reception of reality, which is relevant even for such linguistic constructions that do not directly have markers of temporality, and the ability of such a narrative to configure and reconfigure formats of understanding and meanings of a work of art is emphasized both at the formal and at the content levels. …”
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Mixed nontuberculous mycobacteria in an immunocompromised patient with progressive multifocal leukoencephalopathy by Dr Christoffel Opperman, Dr Janet Scott, Dr Aliasgar Esmail, Dr Sarishna Singh, Mr Yonas Ghebrekristos, Prof Rob warren, Dr Wynand Goosen

“…This case report sheds light on the intricate decision-making process involved in managing NTM mixed disease, addressing both laboratory and treatment impediments. Description: A 40-year-old male presented with constitutional symptoms and chest X-ray changes indicative of structural lung disease, initially suggestive of tuberculosis. …”
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Characterization of severity of hemolytic disease of the fetus and newborn due to Rhesus antigen alloimmunizationAJOG Global Reports at a Glance by Alexis A. Krumme, ScD, Robert Y. Suruki, ScD, Clair Blacketer, MPH, Jill Hardin, PhD, Joel N. Swerdel, PhD, May Lee Tjoa, PhD, Kara B. Markham, MD

“…Most (93.1% Clinformatics®; 93.5% CCAE Database) displayed minimal severity, although in both databases nearly 40% of these neonates still required phototherapy. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…Specifically, LightGCN achieves an accuracy of 0.9210, while DualGNN reaches 0.9285, both falling short of the proposed model’s performance. …”
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Artificial intelligence in hospital infection prevention: an integrative review by Rabie Adel El Arab, Zainab Almoosa, May Alkhunaizi, May Alkhunaizi, Fuad H. Abuadas, Joel Somerville, Joel Somerville

“…Comparative data suggest that while both machine learning and deep learning approaches perform well, some deep learning models may offer slight advantages in complex data environments. …”
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Evaluating methods for integrating single-cell data and genetics to understand inflammatory disease complexity by Hope A. Townsend, Hope A. Townsend, Kaylee J. Rosenberger, Kaylee J. Rosenberger, Lauren A. Vanderlinden, Lauren A. Vanderlinden, Jun Inamo, Jun Inamo, Fan Zhang, Fan Zhang, Fan Zhang

“…First, we applied and compared the results of three recent algorithms, based on pathways (scGWAS), single-cell disease scores (scDRS), or both (scPagwas), according to accuracy/sensitivity and interpretability. …”
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3D‐Printed Titanium Trabecular Scaffolds with Sustained Release of Hypoxia‐Induced Exosomes for Dual‐Mimetic Bone Regeneration by Lincong Luo, Weihan Zheng, Jiaying Li, Tingting Chen, Wanting Xue, Tao Lin, Mingrui Liu, Zi Yan, Jiaxin Yang, Jiamin Li, Jiahao Pu, Yaobin Wu, Konghe Hu, Shiyu Li, Wenhua Huang

“…BTPS is designed using Voronoi algorithms and imaging data, and replicates the geometry and mechanical properties of natural bone. …”
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Optimized Landing Site Selection at the Lunar South Pole: A Convolutional Neural Network Approach by Yongjiu Feng, Haoteng Li, Xiaohua Tong, Pengshuo Li, Rong Wang, Shurui Chen, Mengrong Xi, Jingbo Sun, Yuhao Wang, Huaiyu He, Chao Wang, Xiong Xu, Huan Xie, Yanmin Jin, Sicong Liu

“…Although intelligent algorithms have been increasingly investigated for this purpose, the application of deep learning techniques in landing site selection remains unexplored. …”
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Management and outcome of whole-spine epidural abscesses – institutional case series and systematic review by Erik Schulz, Linda Bättig, Felix C. Stengel, Lorenzo Bertulli, Nader Hejrati, Maximilian Wegener, Carol Strahm, Benjamin Martens, Martin N. Stienen, Stefan Motov

“…Larger multicenter studies are needed to establish reliable treatment algorithms.…”
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Association between pro-inflammatory diet and fecal incontinence: a large population-based study by Haiyang Wang, Haiyang Wang, Zihan Liu, Zihan Liu, Xingfu Lu, Enyu Luan, Enyu Luan, Tingting Dong, Tingting Dong, Can Li, Can Li, Yanni Lv, Erkang Wu, Tao Shen, Tao Shen

“…The receiver operating characteristic (ROC) analyses conducted on both the training and independent validation cohorts demonstrate favorable predictive performance for FI in nearly 10,000 participants. …”
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A Next-generation Exoplanet Atmospheric Retrieval Framework for Transmission Spectroscopy (NEXOTRANS): Comparative Characterization for WASP-39 b Using JWST NIRISS, NIRSpec PRISM,... by Tonmoy Deka, Tasneem Basra Khan, Swastik Dewan, Priyankush Ghosh, Debayan Das, Liton Majumdar

“…Absorption features in both NIRSpec PRISM and MIRI data constrained SO _2 log VMRs to values between −6.25 and −5.73 for all models except equilibrium chemistry. …”
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IKZF1 as a potential therapeutic target for dendritic cell-mediated immunotherapy in IgA nephropathy by Fei Peng, Chunjia Sheng, Jiayi He, Yena Zhou, Yilun Qu, Shuwei Duan, Yinghua Zhao, Jikai Xia, Jie Wu, Guangyan Cai, Lingling Wu, Chuyue Zhang, Xiangmei Chen

“…Receiver operating characteristic (ROC) curve analysis and machine learning algorithms were employed to screen for DC-related diagnostic biomarkers from the dataset. …”
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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Regression and classification models were developed using gradient boosting, random forest, and CatBoost algorithms. Regression models predicted vault height as a continuous variable, while classification models categorized vault heights into binary and multi-class tasks. …”
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Effects of different wearable sensors and locomotion tasks on machine learning-based joint moment prediction by Jonas Weber, Bernd J. Stetter

“…However, comparing different studies investigating various sensors and locomotion tasks can be challenging due to variations in ML algorithms, model evaluation techniques, and reported performance metrics (Gurchiek et al., 2019). …”
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Generation of Spatial Structure of Urban Parks Based on Spatial Analysis of Agent-Based Models by Huizi KONG, Tianming LIU, Jiajie LIAO, Liu CUI

“…ObjectiveThis research aims to leverage the advances of computer algorithms to provide scientific analytical methods for spatial simulation and offer a more objective approach to reflect the natural operational laws of interdependencies between elements in the real physical world for landscape design. …”
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Comparison of Random Survival Forest Based‐Overall Survival With Deep Learning and Cox Proportional Hazard Models in HER‐2‐Positive HR‐Negative Breast Cancer by Wenqi Cai, Yan Qi, Linhui Zheng, Huachao Wu, Chunqian Yang, Runze Zhang, Chaoyan Wu, Haijun Yu

“…Predictive models were developed using five feature sets and three algorithms (Cox PH, RSF, DeepSurv), with feature selection optimized via Concordance index (C‐index). …”
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Innovación en sueño by Laura Vigil, Toni Zapata, Andrea Grau, Marta Bonet, Montserrat Montaña, María Piñar

“…Despite these obstacles, AI and Big Data have the potential to transform medical care for sleep disorders, improving both diagnosis and treatment adherence, provided regulatory and cultural barriers are overcome.…”
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Identification and validation of key biomarkers associated with immune and oxidative stress for preeclampsia by WGCNA and machine learning by Tiantian Yu, Tiantian Yu, Tiantian Yu, Guiying Wang, Guiying Wang, Guiying Wang, Xia Xu, Xia Xu, Xia Xu, Jianying Yan, Jianying Yan, Jianying Yan

“…BackgroundPreeclampsia (PE), a major obstetric disorder marked by dysfunction in both placental and maternal vascular systems, continues to pose critical challenges in global maternal healthcare. …”
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