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GIS vibration signal denoising algorithm based on SVD-IACMD
Published 2024-11-01“…In response to the current situation, an on-site vibration signal denoising diagnosis algorithm based on the singular value decomposition (SVD)-improve adaptive chirp mode decomposition (IACMD) algorithm is proposed. …”
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443
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Prediction of formation pressure in underground gas storage based on data-driven method
Published 2023-05-01“…The optimal warping path is weighted by the proportion of gas injection-production to screen pressure monitoring wells. The supervised learning model of formation pressure forecasting is established by three kinds of machine learning algorithms including extreme gradient boosting (XGBoost), support vector regression (SVR), and long short-term memory network (LSTM). …”
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445
Liquid chromatography-mass spectrometry-based metabolic panels characteristic for patients with prostate cancer and prostate-specific antigen levels of 4–10 ng/mL
Published 2025-03-01“…Based on the identified metabolites, LASSO regression was applied for variable selection, and logistic regression and support vector machine models were developed. Results: The LASSO algorithm’s ability to select variables effectively reduced redundant features and minimized model overfitting. …”
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446
Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study
Published 2025-05-01“…Objective This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain. …”
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447
Preference-based expensive multi-objective optimization without using an ideal point
Published 2025-06-01“…The Gaussian process model is built on the objective functions. In the model-based optimization, the projection distance with upper confidence bound (UCB) is developed as the fitness of solutions for each subproblem. …”
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448
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Global miniaturization of broadband antennas by prescreening and machine learning
Published 2024-11-01“…Our technique includes parameter space pre-screening and the iterative refinement of kriging surrogate models using the predicted merit function minimization as an infill criterion. …”
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450
Applications of Artificial Intelligence in Drug Repurposing
Published 2025-04-01Get full text
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451
The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances
Published 2021-01-01“…The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. …”
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452
Screening for endometriosis: A scoping review of screening measures that could support early diagnosis
Published 2025-07-01“…Despite reporting symptoms, women wait around 11 years before receiving a diagnosis, further interfering with their mental and physical health. Patient reported screening measures can promote faster diagnosis, however their measurement quality remains unknown. …”
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453
Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants
Published 2025-04-01“…For nRDS, biomarkers such as the lecithin/sphingomyelin (L/S) ratio and oxidative stress indicators have been effectively used in innovative diagnostic methods, including attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and high-content screening for ABCA3 modulation. Machine learning algorithms like Partial Least Squares Regression (PLSR) and C5.0 have shown potential in accurately identifying critical health indicators. …”
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454
基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke...
Published 2025-04-01“…After retaining independent features, the least absolute shrinkage and selection operator (LASSO) regression algorithm was used for feature selection and to construct a joint prediction model. …”
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455
Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach
Published 2025-01-01“…Intriguingly, 13 key DEGs were identified across hubs and clusters, highlighting their aberrant expressions in cell cycle regulation, immune responses, and cancer pathways. Biomarker screening via Random Forest (RF) model (selected with PyCaret from multiple models) and validation through t-distributed stochastic neighbor embedding (t-SNE) algorithm, principal component analysis (PCA), and ROC curve analysis employing Logistic Regression and Random Forest, identified 6 key DEGs (TXNRD1, CCNB1, BUB1, CDC20, BUB1B, and CCNA2) as promising biomarkers (AUC > 0.7) for clade IIb infection. …”
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456
Design of public space guide system based on augmented reality technology
Published 2025-07-01“…The research is based on imaging techniques using augmented reality technology and camera image capture. Then, it uses screen error algorithms and scale-invariant feature transformation operators to test the quality of scene spatial models. …”
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A Web-Based Interface That Leverages Machine Learning to Assess an Individual’s Vulnerability to Brain Stroke
Published 2025-01-01“…We compare a range of algorithms-including traditional classifiers and deep learning models-and report comprehensive performance metrics (accuracy, precision, recall, F1-score, and AUC-ROC) for each. …”
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Research on Characteristics and Influencing Factors of High Temperature Disaster Risk in Wuhan Based on Local Climate Zone
Published 2025-01-01“…Furthermore, highly correlated LCZ types are screened out under the optimal size, the multicollinearity of all LCZ landscape pattern indices is examined and those with multicollinearity are excluded. …”
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CELIAC DISEASE SCREENING IN A LARGE DOWN SYNDROME COHORT: COMPARISON OF DIAGNOSTIC YIELD OF DIFFERENT SEROLOGICAL SCREENING TESTS
Published 2023-10-01“…This study aimed to estimate the prevalence of CD in DS patients and compare the diagnostic performance of the screening algorithms. Material and Method: A cohort of 1117 DS patients were included. …”
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