Unveiling lipoprotein subfractions signature in high-FNPO PCOS: implications for PCOM diagnosis and risk assessment using advanced machine learning models by Xueqi Yan, Ziyi Yang, Hui Zhao, Gengchen Feng, Shumin Li, Yimeng Li, Yu Sun, Jinlong Ma, Han Zhao, Xueying Gao, Shigang Zhao

“…Ten machine learning algorithms and recursive feature elimination with logistic regression were used to construct the effective model to predict PCOM based on the new guideline. …”
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A Convolutional Neural Network–Based Approach for Detecting Solar System Objects in Wide-field Imaging by Aram Lee, J. J. Kavelaars, Hossen Teimoorinia, Wesley Fraser, Edward Ashton

“…A separate regression model predicted the source locations with a mean absolute error of ±1.5 pixels for sources with a signal-to-noise ratio (SNR) of 16.5 or higher. …”
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Research on Stability of Removal Function in Figuring Process of Mandrel of X-Ray-Focusing Mirror with Variable Curvature by Jiadai Xue, Yuhao Li, Mingyang Gao, Dongyun Gu, Yanlin Wu, Yanwen Liu, Yuxin Fan, Peng Zheng, Wentao Chen, Zhigao Chen, Zheng Qiao, Yuan Jin, Fei Ding, Yangong Wu, Bo Wang

“…This model predicts the compliance figuring process of variable-curvature symmetrical mandrels for X-ray grazing incidence mirrors by utilizing planar tool influence functions. …”
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Identification of Clusters in a Population With Obesity Using Machine Learning: Secondary Analysis of The Maastricht Study by Maik JM Beuken, Melanie Kleynen, Susy Braun, Kees Van Berkel, Carla van der Kallen, Annemarie Koster, Hans Bosma, Tos TJM Berendschot, Alfons JHM Houben, Nicole Dukers-Muijrers, Joop P van den Bergh, Abraham A Kroon, Iris M Kanera

“…To identify a subset of distinct, minimally redundant, predictive variables, we used the statistically equivalent signature algorithm. …”
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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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Automated EEG background analysis to identify neonates with hypoxic-ischemic encephalopathy treated with hypothermia at risk for adverse outcome: A pilot study by Anneleen Dereymaeker, Vladimir Matic, Jan Vervisch, Perumpillichira J. Cherian, Amir H. Ansari, Ofelie De Wel, Paul Govaert, Maarten De Vos, Sabine Van Huffel, Gunnar Naulaers, Katrien Jansen

“…Keywords: hypoxic-ischemic encephalopathy, automated EEG analysis, dynamic Interburst Interval, outcome prediction…”
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Risk Factors for Gastrointestinal Bleeding in Patients With Acute Myocardial Infarction: Multicenter Retrospective Cohort Study by Yanqi Kou, Shicai Ye, Yuan Tian, Ke Yang, Ling Qin, Zhe Huang, Botao Luo, Yanping Ha, Liping Zhan, Ruyin Ye, Yujie Huang, Qing Zhang, Kun He, Mouji Liang, Jieming Zheng, Haoyuan Huang, Chunyi Wu, Lei Ge, Yuping Yang

“…ObjectiveThis study aimed to develop and validate a machine learning (ML)–based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support. …”
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Pharmacological potential of 6,11-dihydro[1,2,4]triazolo[4’,3’:1,6]-pyrido[3,4-b]-5-carboxylic acid and its esters by S. O. Fedotov, A. S. Hotsulia

“…The molecular docking method, based on computational algorithms, has been used to predict and study interactions, including the identification of potential binding sites, estimation of energy parameters and spatial configuration of molecules. …”
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Molecular subtype of recurrent implantation failure reveals distinct endometrial etiology of female infertility by Jing Yang, Lingtao Yang, Ying Zhou, Fengyang Cao, Hongkun Fang, Huan Ma, Jun Ren, Chunyu Huang, Lianghui Diao, Qiyuan Li, Qionghua Chen

“…A molecular classifier (MetaRIF) was developed using the optimal F-score from 64 combinations of machine learning algorithms. Candidate therapeutic compounds were predicted using the Connectivity Map (CMap) database. …”
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Pre-Hospital Point-of-Care Troponin: Is It Possible to Anticipate the Diagnosis? A Preliminary Report by Cristian Lazzari, Sara Montemerani, Cosimo Fabrizi, Cecilia Sacchi, Antoine Belperio, Marilena Fantacci, Giovanni Sbrana, Agostino Ognibene, Maurizio Zanobetti, Simone Nocentini

“…Both the Atellica VTLi and the Elecsys method showed high negative predictive value (NPV), indicating that a negative troponin result effectively ruled out AMI in most cases. …”
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Galaxy Spectroscopy without Spectra: Galaxy Properties from Photometric Images with Conditional Diffusion Models by Lars Doorenbos, Eva Sextl, Kevin Heng, Stefano Cavuoti, Massimo Brescia, Olena Torbaniuk, Giuseppe Longo, Raphael Sznitman, Pablo Márquez-Neila

“…Here, we report the development of a generative artificial intelligence (AI) method capable of predicting optical galaxy spectra from photometric broadband images alone. …”
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A three-subtype prognostic classification based on base excision repair and oxidative stress genes in lung adenocarcinoma and its relationship with tumor microenvironment by Wen Rao, Qin Zhang, Xiaoyan Dai, Yuxin Yang, Zhang Lei, Xunjie Kuang, He Xiao, Jianwu Zhu, Yanli Xiong, Dong Wang, Lujie Yang

“…C2 was also associated with an improved survival outcome compared with C1 and C3, and this finding was validated in 978 samples from four independent GEO datasets and 52 samples at our institution by the NTP algorithm. The three-subtype classifications based on BER and oxidative stress gene expression offers potential for predicting the survival and response to immunotherapy of LUAD patients.…”
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LMO2 confers value as a potential immunotherapy marker in pan-cancer analysis and inhibits progression of Clear Cell Renal Cell Carcinoma by Huiping Wang, Cong Wang, Jia Wei, Xuan’er Zhao, Xuemei Yang, Renren Li, Mengmeng Li, Zhansheng Zhu

“…Immune microenvironment associations were evaluated through Pearson correlation coefficients and TIMER algorithm validation. Subsequent functional enrichment analyses and predictive regulator identification were performed to delineate signaling pathways in ccRCC. …”
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Spatiotemporal pattern and driving factors of atmospheric CO2 concentrations based on satellite remote sensing from 2001 to 2022 in central Yunnan plateau by Yunling He, Xiaohua Zhang, Ning Pu, Chunyan Wu, Wu Tang

“…Using Geographically and Temporally Weighted Regression (GTWR) and Geographical detector (GD), a prediction model was established to explore the complex relationship between 14 driving factors of 3 different types (including urban spatial configuration, natural factors and socioeconomic factors) and the annual CO2 concentrations. …”
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CcpA-mediated regulation of cellular energy metabolism in the ruminal bacterium Streptococcus bovis by Yunan Weng, Yaqian Jin, Wenze Zhang, Lihong Wang, Hongrong Wang

“…Orthogonal projections to latent structures discriminant analysis (OPLS-DA) further distinguished between each pair of groups. KEGG prediction indicated that the abundance and enrichment of metabolites were primarily involved in carbon metabolism, amino acid metabolism, and nucleotide metabolomics. …”
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Comparing and Combining Artificial Intelligence and Spectral/Statistical Approaches for Elevating Prostate Cancer Assessment in a Biparametric MRI: A Pilot Study by Rulon Mayer, Yuan Yuan, Jayaram Udupa, Baris Turkbey, Peter Choyke, Dong Han, Haibo Lin, Charles B. Simone

“…Combining Z-SSMNet with spectral/statistical approaches significantly enhanced tumor grade prediction, possibly providing an alternative to current prostate tumor assessment.…”
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Biomarkers of microvascularture by ultra Micro-angiography (UMA) assist to identify papillary thyroid carcinoma (PTC) with atypia of undetermined significance by Qingsong Wang, Zhewei Li, Jie Zhang, Sijie Zhang, Lijun Wang, Hongjian Yao, Hong Zhang, Jing Li, Shuo Wang, Jinglai Sun, Wenhui Zhang, Hui Yu

“…Conclusions This study demonstrated the potential value of microvasculature in the prediction of PTC in AUS Cases and improved the performance of ultrasound examination. …”
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Using Calibration Transfer Strategy to Update Hyperspectral Model for Quantitating Soluble Solid Content of Blueberry Across Different Batches by Biao Chen, Xuhuang Huang, Shenwen Tan, Guangjun Qiu, Huaiyin Lin, Xuejun Yue, Junzhi Chen, Wenshan Zhong, Xuantian Li, Le Zhang

“…This high-performance model could achieve a high determination coefficient (<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msubsup><mi mathvariant="normal">R</mi><mi mathvariant="normal">P</mi><mn>2</mn></msubsup></mrow></semantics></math></inline-formula>) of 0.8965 and a low root mean square error of prediction (RMSEP) of 0.3707 °Brix. Using the sample dataset for the year 2025, the hyperspectral model was updated by the semi-supervised parameter-free calibration enhancement (SS-PFCE) algorithm. …”
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Comparison of four different assays to evaluate cellular-mediated immunity against cytomegalovirus in solid organ transplantation by Angela Casas-Parra, Angela Casas-Parra, Hendrik Veltman, Alba Romero-Caballero, Alba Romero-Caballero, Rosana Gelpi-Remiro, Rosana Gelpi-Remiro, Marc Boigues-Pons, Imán Allalou, Ian Linares-Pardo, Anna Vila-Santandreu, Anna Vila-Santandreu, Eva Martínez-Cáceres, Eva Martínez-Cáceres, Eva Martínez-Cáceres, María Iglesias-Escudero, María Iglesias-Escudero, María Iglesias-Escudero

“…In this context, measuring CMV-specific cell-mediated immunity (CMI) has proven to be a valuable tool, with high negative predictive value (NPV) for the absence of CMV viremia in patients with positive tests. …”
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The value of a combined model based on ultra-radiomics and multi-modal ultrasound in the benign-malignant differentiation of C-TIRADS 4A thyroid nodules: a prospective multicenter... by Shuai Cui, Qifan Liu, Hailong Wang, Husha Li, Wei Li, Chenlong Li, Leilei Bi, Yang Mu, Wenjing Guo, Jundong Yao, Zhoulong Zhang

“…The predictive efficiency and accuracy of these models were evaluated using Receiver Operating Characteristic (ROC) curves, calibration curves, and Decision Curve Analysis (DCA). …”
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