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Development and Clinical Validation of Visual Inspection With Acetic Acid Application-Artificial Intelligence Tool Using Cervical Images in Screen-and-Treat Visual Screening for Ce...
Published 2024-12-01“…The perceived challenge rate for false positives was 20%.CONCLUSIONThis novel cervical image–based VIA-AI algorithm showed promising results in real-life settings, and could help minimize overtreatment in single-visit VIA screening and treatment programs in resource-constrained situations.…”
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502
Screening of serum biomarkers in patients with PCOS through lipid omics and ensemble machine learning.
Published 2025-01-01“…Three machine learning models, logistic regression, random forest, and support vector machine, showed that screened biomarkers had better classification ability and effect. …”
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503
Inferring regulatory networks by combining perturbation screens and steady state gene expression profiles.
Published 2014-01-01“…The proposed approach is based on a three-step algorithm to estimate the underlying directed but cyclic network, that uses as input both perturbation screens and steady state gene expression data. …”
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504
Development of Electronic Nose as a Complementary Screening Tool for Breath Testing in Colorectal Cancer
Published 2025-02-01“…We then used machine learning algorithms to develop predictive models and provided the estimated accuracy and reliability of the breath testing. (3) Results: We enrolled 77 patients, with 40 cases and 37 controls. …”
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505
Design and evaluation of screening and self-care (mobile) application for oral and dental problems and emergencies
Published 2025-01-01“…Materials and method: A system made up of web and mobile apps is proposed and evaluated for screening and self-care of oral and dental problems and for providing advice on dental emergencies and therapeutic measures. …”
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506
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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507
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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508
Improvement of the Diagnostics of the Fetus Heart Anomalies During a Routine Screening Ultrasound Examination
Published 2014-09-01“…In our opinion, the prenatal detection of congenital heart defects strongly depends on the algorithm of conducting a fetal heart study in the screening regimen. …”
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509
Short-Term Photovoltaic Power Combined Prediction Based on Feature Screening and Weight Optimization
Published 2025-01-01“…Aiming at the problem of low prediction accuracy caused by the intermittent and fluctuating characteristics of photovoltaic power, a short-term photovoltaic power combined prediction method based on feature screening and weight optimization is proposed. Firstly, K-means is used to cluster the photovoltaic power; Secondly, CEEMDAN is used to decompose photovoltaic power and wavelet decomposition is used to decompose irradiance, and sample entropy and K-means are used to reconstruct each component of photovoltaic power into high, intermediate, and low frequency terms; Then, Spearman’s correlation coefficient is used to calculate the correlation between each meteorological factor and the decomposed irradiance component and the high, intermediate, and low frequency terms of photovoltaic power, and the feature selection is carried out; Then, CNN-BiLSTM-Attention is used to predict the high frequency term, LSTM is used to predict the intermediate frequency and low frequency terms, and the results are superimposed to obtain the preliminary prediction value; Finally, the dung beetle algorithm is used to optimize the weights of the initial prediction values of the training set of high, intermediate, and low frequency terms, and the optimal weight is substituted into the test set to obtain the final prediction result. …”
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510
Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images
Published 2025-01-01Get full text
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511
Domain name generation algorithm based on improved Markov chain
Published 2024-11-01“…Then, the improved Markov model algorithm was used to analyze the filtered data, and new subdomain names were generated and added to the result set. …”
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512
Laryngeal cancer diagnosis based on improved YOLOv8 algorithm
Published 2025-01-01“…A novel multiscale enhanced convolution module has been introduced to improve the model’s feature extraction capabilities for small-sized targets. …”
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513
Electricity Load Forecasting Method Based on the GRA-FEDformer Algorithm
Published 2025-07-01Get full text
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514
Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening.
Published 2015-01-01“…Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening.…”
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515
Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction
Published 2025-06-01“…Currently, several specialized databases have been established, providing rich resources for algorithmic model training. Furthermore, multi-source bioinformatics data such as genomics, transcriptomics and proteomics are also widely used to predict antimicrobial peptides, with a view to identifying peptides with potential antimicrobial activity more accurately. …”
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516
Analysis of E-Commerce Marketing Strategy Based on Xgboost Algorithm
Published 2023-01-01“…This paper reviews the current literature on e-commerce marketing and then analyzes the feasibility of precision marketing in e-commerce market in the new media era. In order to screen potential consumers and improve the success rate of precision marketing, this paper establishes a prediction model for precision marketing of bank credit cards. …”
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517
Round reduction-based fault attack on SM4 algorithm
Published 2016-10-01“…A novel method of fault attack based on round reduction against SM4 algorithm was proposed.Faults were in-jected into the last four rounds of the SM4 encryption algorithm,so that the number of the algorithm's rounds can be re-duced.In known-ciphertext scenario,four traces are enough to recover the total 128 bit master key by screening these faults easily.The proposed attack is made to an unprotected SM4 smart card.Experiment shows that this attack method is efficient,and which not only simplifies the existing differential fault attack,but also improves the feasibility of the attack.…”
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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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520
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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