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861
Tool wear prediction based on XGBoost feature selection combined with PSO-BP network
Published 2025-01-01“…Experimental results show that PSO outperforms other algorithms in training the tool wear prediction model, with XGBoost feature selection reducing model construction time by 57.4% and increasing accuracy by 63.57%, demonstrating superior feature selection capabilities over Decision Tree, Random Fores, Adaboost and Extra Trees. …”
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862
Optimizing deep learning for accurate blood cell classification: A study on stain normalization and fine-tuning techniques
Published 2025-01-01“…BACKGROUND: Deep learning’s role in blood film screening is expanding, with recent advancements including algorithms for the automated detection of sickle cell anemia, malaria, and leukemia using smartphone images. …”
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863
Significance of Immune-Related Genes in the Diagnosis and Classification of Intervertebral Disc Degeneration
Published 2022-01-01“…Then, we utilized a random forest (RF) model to screen six candidate IRGs to predict the risk of IDD. …”
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864
Efficient secure federated learning aggregation framework based on homomorphic encryption
Published 2023-01-01“…In order to solve the problems of data security and communication overhead in federated learning, an efficient and secure federated aggregation framework based on homomorphic encryption was proposed.In the process of federated learning, the privacy and security issues of user data need to be solved urgently.However, the computational cost and communication overhead caused by the encryption scheme would affect the training efficiency.Firstly, in the case of protecting data security and ensuring training efficiency, the Top-K gradient selection method was used to screen model gradients, reducing the number of gradients that need to be uploaded.A candidate quantization protocol suitable for multi-edge terminals and a secure candidate index merging algorithm were proposed to further reduce communication overhead and accelerate homomorphic encryption calculations.Secondly, since model parameters of each layer of neural networks had characteristics of the Gaussian distribution, the selected model gradients were clipped and quantized, and the gradient unsigned quantization protocol was adopted to speed up the homomorphic encryption calculation.Finally, the experimental results show that in the federated learning scenario, the proposed framework can protect data privacy, and has high accuracy and efficient performance.…”
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865
Integrated analysis of single-cell RNA-seq and spatial transcriptomics to identify the lactylation-related protein TUBB2A as a potential biomarker for glioblastoma in cancer cells...
Published 2025-06-01“…Notably, the expression levels of these three hub genes and the lactylation level of TUBB2A in GBM tissues were significantly higher compared to those in normal tissues.ConclusionsWe propose and validate a IQR lactylation screening method that provides potential insights for GBM therapy and an effective framework for developing gene screening models applicable to other diseases and pathogenic mechanisms.…”
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866
IMPROVEMENT OF ADAPTATION TO STRUCTURES REMOVABLE DENTURES IN PATIENTS WITH ISCHEMIC HEART DISEASE
Published 2018-03-01“…The proposed health care was a complex algorithm to use: softener oral "Corsodyl" - 3-5 times a day after meals; clean teeth and dentures 2 times a day (morning and bedtime) toothpaste "Parodontax" and the bath solution Rinhra 3-5 times a day, with dryness in the mouth For the functional assessment made dentures were designed by us and proposed to use two methods of assessing patients to adapt designs removable dentures: • Objective evaluation - "Method of determining the degree of adaptation to the designs of removable dentures," Ukraine patent for utility model №101852 of 12.10.15; • Subjective evaluation - "Method of accelerated determination adaptation of patients to removable dentures designs using screening test" certificate of registration of copyright Ukraine №59280 15.04.2015. …”
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867
Evaluation of liver fibrosis in patients with metabolic dysfunction-associated steatotic liver disease using ultrasound controlled attenuation parameter combined with clinical feat...
Published 2024-10-01“…Features were selected using the Boruta algorithm, and a predictive model combining CAP and clinical features was constructed. …”
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868
Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network
Published 2024-11-01“…The trained model performed similarly to state-of-the-art lumbar spine segmentation models, with an average DSC value of 0.914 ± 0.007 for the vertebrae and 0.902 for the spinal canal. …”
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869
Automated interpretation of influenza hemagglutination inhibition (HAI) assays: Is plate tilting necessary?
Published 2017-01-01“…In a side-by-side comparison study performed during FDA's biannual serological screening process for influenza viruses, titer calls for more than 2200 serum samples were made by the Cypher One automated hemagglutination analyzer without tilting and by an expert human with tilting. …”
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870
CALCULATION OF OBJECTS THERMAL IMAGING PARAMETERS FROM UNMANNED AERIAL VEHICLES
Published 2020-03-01“…Estimates were made for two cases: observation of a thermal image by an operator on a display screen and for the case when an electronic image is analyzed by a threshold algorithm with no operator engaged. …”
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871
Automated whole animal bio-imaging assay for human cancer dissemination.
Published 2012-01-01“…Moreover, RNA interference establishes the metastasis-suppressor role for E-cadherin in this model. This automated quantitative whole animal bio-imaging assay can serve as a first-line in vivo screening step in the anti-cancer drug target discovery pipeline.…”
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872
3D Film Animation Image Acquisition and Feature Processing Based on the Latest Virtual Reconstruction Technology
Published 2021-01-01“…Finally, the target 3D face is reconstructed using the feature points of the target face for model matching. The experimental results show that the algorithm reconstructs faces with high realism and accuracy, and the algorithm can reconstruct expression faces.…”
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873
Technical Code Analysis of Geomagnetic Flaw Detection of Suppression Rigging Defect Signal Based on Convolutional Neural Network
Published 2024-12-01“…The single-stage object detection algorithm YOLOv5 (You Only Look Once) based on convolutional neural network model calculation is used, the scale detection layer and positioning loss function of the YOLOv5 algorithm are improved and optimized, and the improved YOLOv5 algorithm is used for experiments. …”
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874
Time-Distributed Vision Transformer Stacked With Transformer for Heart Failure Detection Based on Echocardiography Video
Published 2024-01-01“…This study proposed a novel deep learning model consisting of a time-distributed vision transformer stacked with a transformer. …”
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875
Numerical analysis method of stress wave transmission attenuation of coal and rock structural plane
Published 2024-11-01“…The simulation and machine learning of stress wave transmission in the experimental process of Split Hopkinson Pressure Bar (SHPB) were carried out by combining the Barton-Bandis nodal ontology model, UDEC discrete element simulation and Gray Wolf Algorithm optimized BP neural network technology. …”
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876
Optimization of the Canopy Three-Dimensional Reconstruction Method for Intercropped Soybeans and Early Yield Prediction
Published 2025-03-01“…Point cloud preprocessing was refined through the application of secondary transformation matrices, color thresholding, statistical filtering, and scaling. Key algorithms—including the convex hull algorithm, voxel method, and 3D α-shape algorithm—were optimized using MATLAB, enabling the extraction of multi-dimensional canopy parameters. …”
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877
Preoperative prediction of pituitary neuroendocrine tumor invasion using multiparametric MRI radiomics
Published 2025-01-01“…Radiomics features were extracted from the manually delineated regions of interest in T1WI, T2WI and CE-T1, and the best radiomics features were screened by LASSO algorithm. Single radiomics model (T1WI, T2WI, CE-T1) and combined radiomics model (T1WI+T2WI+CE-T1) were constructed respectively. …”
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878
Noninvasive prediction of meningioma brain invasion via multiparametric MRI⁃based brain⁃tumor interface radiomics
Published 2025-03-01“…Through five⁃fold cross⁃validation in the training set and evaluation in the testing set, comparative analysis of the predictive performance of 18 model⁃thickness combinations (6 ML algorithms × 3 BTI thicknesses) showed that the XGBoost model constructed with a 1.00 cm BTI thickness demonstrated exceptional performance. …”
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879
Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review
Published 2025-05-01“…MethodsUsing Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modelling Studies (CHARMS), and Prediction model Risk of Bias Assessment Tool (PROBAST) tools, we conducted a comprehensive review of studies applying ML and DL models for leptospirosis detection and prediction, examining algorithm performance, data sources, and validation approaches. …”
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880
To accurately predict lymph node metastasis in patients with mass-forming intrahepatic cholangiocarcinoma by using CT radiomics features of tumor habitat subregions
Published 2025-02-01“…Using information from the arterial and venous phases of multisequence CT images, tumor habitat subregions were delineated through the K-means clustering algorithm. Radiomic features were extracted and screened, and prediction models based on different subregions were constructed and compared with traditional intratumoral models. …”
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