Calibration and surrogate model-based sensitivity analysis of crystal plasticity finite element models by Hugh Dorward, David M. Knowles, Eralp Demir, Mahmoud Mostafavi, Matthew J. Peel

“…Crystal plasticity models are powerful tools for predicting the deformation behaviour of polycrystalline materials accounting for underlying grain morphology and texture. …”
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Closing the Open System by Nina Stener Jørgensen, Guillaume Laplante-Anfossi

“…The review of the programme questions how the probability distributions Schöffer included in the algorithm to ensure a random treatment of predictable city data was imagined to avoid stagnation, repetition and programmatic saturation, all elements essential to maintaining the tower’s open framework. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…The SHAP algorithm was further used to quantify the contribution of each gene based on cell death features to the prediction of sepsis. …”
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INFLAMMATION's cognitive impact revealed by a novel "Line of Identity" approach. by Donald R Royall, Raymond F Palmer

“…This algorithm might be applied to any dementia-related biomarker making the psychometric estimation of individual biomarker effects feasible without biomarker assessment. …”
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The Prognostic Significance of TMSB4X in Glioma Patients by Li S, Fan T, Hao Z, Zhang Z, Han X, Li J, Wang Y, Zhou H, Xue X

“…The top 50 core genes were then screened using the cyto Hubba algorithm, these genes were analyzed using The Gene Ontology Database (GO) and the Kyoto Encyclopedia of Genes and Genomes (KEGG). …”
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Automated ejection fraction and risk stratification in cardiomyopathy patients with diverse LV geometry using 2D echocardiography by Ziwei Zhu, Ke Fan, Shuyuan Zhang, Tingting Hu, Jingyi Li, Ze Zhao, Ye Jin, Shuyang Zhang

“…LASSO regression identified predicted LVEF, E/e′ ratio, and age as significant predictors, with AUC values of 0.833 (CR), 0.695 (CH), and 0.938 (EH) for adverse outcomes prediction. …”
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Machine learning-based prognostic model for bloodstream infections in hematological malignancies using Th1/Th2 cytokines by Qin Li, Nan Lin, Zuheng Wang, Yuexi Chen, Yuli Xie, Xuemei Wang, Jirui Tang, Yuling Xu, Min Xu, Na Lu, Yiqian Huang, Jiamin Luo, Zhenfang Liu, Li Jing

“…The predictive model was developed by integrating Th1/Th2 cytokines with clinical features, aiming to enhance the accuracy of 30-day mortality prediction. …”
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Inflammatory markers mediate the association between alternative adiposity indices and mortality in patients with rheumatoid arthritis: data from NHANES 1999–2018 by Feng Luo, Jia-jie Guo, Xue-mei Yuan, Heng Zhou, Qiu-yi Wang, Chang-ming Chen, Xue-ming Yao, Wu-kai Ma

“…Traditional obesity indicators inadequately predict the mortality risk in this population. Thus, the research aimed to evaluate new obesity indicators to explore their close association with RA mortality. …”
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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

“…Based on the random forest algorithm, glutamine and UDP-GlcNac were identified as biomarkers under varying glucose conditions and in the presence or absence of ccpA. …”
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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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Intelligent generative design: a transfer learning-enhanced bidirectional mapping framework for customised parametric structural design by Jiajie Hu, Yayun Wang, Hua Tian, Peng Zheng, Liang Chi, Lulu Xue, Qian Su, Qing Jiang, Yong He, Lan Li, Liya Zhu

“…We employ a genetic algorithm to optimise a back-propagation neural network (GA-BPNN) for forward prediction of elastic modulus from structural parameters (porosity, pore size). …”
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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

“…Firstly, an open-source artifact suppression algorithm, which combined a multi-scale Frangi filter and TOPHAT operation, was proposed for the segmentation of micro-vessels in Ultra Micro-Angiography (UMA) images. …”
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Sustainable analysis of COVID-19 Co-packaged paxlovid: exploring advanced sampling techniques and multivariate processing tools by Shymaa S. Soliman, Nisreen F Abo- Talib, Mohamed R. Elghobashy, Mona A. Abdel Rahman

“…Abstract The drawbacks of random sampling not only hinder the development of more reliable and efficient methods but also weaken their accuracy, predictive abilities, and validity across several domains. …”
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Computer-guided design of novel nitrogen-based heterocyclic sphingosine-1-phosphate (S1P) activators as osteoanabolic agents by Rattanawan Tangporncharoen, Chuleeporn Phanus-Umporn, Supaluk Prachayasittikul, Chanin Nantasenamat, Veda Prachayasittikul, Aungkura Supokawej

“…QSAR modeling was performed using multiple linear regression (MLR) algorithm to successfully obtain two models with good predictive performance. …”
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Development of a Diagnostic Model for Focal Segmental Glomerulosclerosis: Integrating Machine Learning on Activated Pathways and Clinical Validation by Ge Y, Liu X, Shu J, Jiang X, Wu Y

“…We then developed a highly accurate diagnostic model by integrating nine machine learning algorithms into 101 combinations, achieving near-perfect AUC values across training, validation, and external cohorts. …”
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A Novel Deep Learning Architecture for Agriculture Land Cover and Land Use Classification from Remote Sensing Images Based on Network-Level Fusion of Self-Attention Architecture by Hussain Mobarak Albarakati, Muhammad Attique Khan, Ameer Hamza, Faheem Khan, Naoufel Kraiem, Leila Jamel, Latifah Almuqren, Roobaea Alroobaea

“…Numerous advantages for sustainable agricultural applications, including yield prediction, crop monitoring, and climate change adaptation, can be obtained from RS and artificial intelligence. …”
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Machine Learning Models Decoding the Association Between Urinary Stone Diseases and Metabolic Urinary Profiles by Lin Ma, Yi Qiao, Runqiu Wang, Hualin Chen, Guanghua Liu, He Xiao, Ran Dai

“…Our analyses revealed that the Random Forest algorithm exhibited the highest predictive accuracy, with AUC values of 0.809 for kidney stones, 0.99 for ureter stones, and 0.775 for multiple location stones. …”
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Clinical features and serum biomarkers in HIV immune reconstitution inflammatory syndrome after cryptococcal meningitis: a prospective cohort study. by David R Boulware, David B Meya, Tracy L Bergemann, Darin L Wiesner, Joshua Rhein, Abdu Musubire, Sarah J Lee, Andrew Kambugu, Edward N Janoff, Paul R Bohjanen

“…An algorithm based on seven pre-ART serum biomarkers was a robust tool for stratifying high (83%), moderate (48%), and low risk (23%) for IRIS in the cohort. …”
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Development of a method for differential diagnosis of iron deficiency anemia and anemia of chronic disease based on demographic data and routine laboratory tests using machine lear... by N. V. Varekha, N. I. Stuklov, K. V. Gordienko, R. R. Gimadiev, O. B. Shchegolev, S. N. Kislaya, E. V. Gubina, A. A. Gurkina

“…To select an appropriate artificial intelligence algorithm for predicting serum ferritin (SF) levels and to evaluate its applicability for differential diagnosis of iron deficiency anemia and anemia of chronic diseases.   …”
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Numerical model of surface morphology and solid-liquid contact angle in wire electrical discharge machining by Zhi Chen, Yifei Zhou, Zefeng Yang, Zhizhong Zhang, Jian Li, Guojun Zhang, Fenglin Han

“…The established numerical model has been experimentally verified to have high prediction accuracy (the relative error less than 4%). …”
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