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Research on thyroid nodule segmentation algorithm based on improved U-Net model
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Multi-Objective Parameter Optimization of Rotary Screen Coating Process for Structural Plates in Spacecraft
Published 2024-11-01Subjects: “…multi-objective optimization algorithm…”
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METHOD FOR NUMERICAL MODELING OF UNSTEADY SEPARATED FLOW AROUND AIRFOILS MOVING CLOSE TO FLAT SCREEN
Published 2017-05-01“…Three different ways of flow modeling (mirror method, fixed or movable screens) were tested. …”
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Pregnancy probability prediction models based on 5 machine learning algorithms and comparison of their performance
Published 2025-06-01“…In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions, feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set. Five algorithms, that is, Logistic Regression, Naive Bayes, Random Forest, Gradient Boosting Machine, and Support Vector Machine, were used to construct preconception outcome prediction models, and the parameters of each model were optimized using random search combined with grid search. …”
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Fast Modelling Algorithm for Realistic Three-Dimensional Human Face for Film and Television Animation
Published 2021-01-01“…Aiming at the face photos of film and television animation, this paper proposes a new fast three-dimensional (3D) face modelling algorithm. First of all, based on the LBF algorithm, this paper proposes a multifeature selection idea to automatically detect multiple features of the face. …”
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Modeling the prediction of spontaneous rupture and bleeding in hepatocellular carcinoma via machine learning algorithms
Published 2025-07-01“…Abstract This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the predictive efficacy of the model. …”
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Predictive Models for Educational Purposes: A Systematic Review
Published 2024-12-01“…The findings show that ML algorithms consistently outperform traditional models due to their capacity to handle large, non-linear datasets and continuously enhance predictive accuracy as new patterns emerge. …”
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Revolutionizing pharmacology: AI-powered approaches in molecular modeling and ADMET prediction
Published 2025-12-01“…It outlines the evolution of computational chemistry and the transformative role of AI in interpreting complex molecular data, automating feature extraction, and improving decision-making across the drug development pipeline. Core AI algorithms support vector machines, random forests, graph neural networks, and transformers are examined for their applications in molecular representation, virtual screening, and ADMET property prediction. …”
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Predictive machine-learning model for screening iron deficiency without anaemia: a retrospective cohort study
Published 2025-08-01“…Subgroup analysis showed that model accuracy varied by sex and age, with lower performance in premenopausal women (AUC 0.736) compared with postmenopausal women (AUC 0.793) and men (AUC of 0.832 in those under 60 years and 0.806 in those aged 60 and above).Conclusions The ML model provides an effective approach to screening for IDWA using readily available EHR data. …”
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A bayesian network model for neurocognitive disorders digital screening in Chinese population: development and validation study
Published 2025-08-01“…Among 1,626,817 individuals initially screened, 4,518 diagnosed NCD cases were included for model building and validation. …”
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Post-processing methods for mitigating algorithmic bias in healthcare classification models: An extended umbrella review
Published 2025-08-01“…Future research should empirically compare post-processing methods on binary classification models using real-world healthcare data. As commercial algorithms proliferate, health systems require proven, achievable strategies to maximize fairness.…”
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Developing an Algorithm for Detecting Suspicious Trades in Tehran Stock Exchange Based on Spoof Trading Model
Published 2023-03-01“…More specifically, this paper studies manipulated stocks by looking at market microstructure (intraday transactions) and aims to introduce an algorithm for detecting suspicious trades so that regulators can detect them beforehand. …”
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An evolutionary model-based algorithm for accurate phylogenetic breakpoint mapping and subtype prediction in HIV-1.
Published 2009-11-01“…Our Subtype Classification Using Evolutionary ALgorithms (SCUEAL) procedure is shown to perform very well in a variety of simulation scenarios, runs in parallel when multiple sequences are being screened, and matches or exceeds the performance of existing approaches on typical empirical cases. …”
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Screening benzimidazole derivatives for atypical antipsychotic activity
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Developing a novel aging assessment model to uncover heterogeneity in organ aging and screening of aging-related drugs
Published 2025-07-01“…Furthermore, a random walk algorithm and a weighted integration approach combining gene set enrichment analysis were implemented to systematically screen potential drugs for mitigating multi-organ aging. …”
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Development and Internal Validation of a Machine Learning-Based Colorectal Cancer Risk Prediction Model
Published 2025-03-01“…<b>Methods:</b> We analyzed data from 154,887 adults, aged 55–74 years, who participated in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. A risk prediction model was built using the Light Gradient Boosting Machine (LightGBM) algorithm. …”
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Bone scintigraphy based on deep learning model and modified growth optimizer
Published 2024-10-01“…The results and statistical analysis revealed that the proposed GOAOA algorithm as an FS technique outperforms the other FS algorithms employed in this study.…”
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Semiparametric Transformation Models with a Change Point for Interval-Censored Failure Time Data
Published 2025-08-01“…Model parameters are estimated via the EM algorithm, with the change point identified through a profile likelihood approach using grid search. …”
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