Changes in sarcopenia and incident cardiovascular disease in prospective cohorts by Qingyue Zeng, Lijun Zhao, Qian Zhong, Zhenmei An, Shuangqing Li

“…Sarcopenia status was assessed using the 2019 Asian Working Group for Sarcopenia (AWGS) algorithm and categorized as non-sarcopenia, possible sarcopenia, or sarcopenia. …”
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An endoscopic ultrasound-based interpretable deep learning model and nomogram for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer by Nan Yi, Shuangyang Mo, Yan Zhang, Qi Jiang, Yingwei Wang, Cheng Huang, Shanyu Qin, Haixing Jiang

“…The least absolute shrinkage and selection operator algorithm was employed to reduce the dimensionality of deep learning (DL) features extracted from pre-standardized EUS images. …”
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Predictive value of dendritic cell-related genes for prognosis and immunotherapy response in lung adenocarcinoma by Zihao Sun, Mengfei Hu, Xiaoning Huang, Minghan Song, Xiujing Chen, Jiaxin Bei, Yiguang Lin, Size Chen

“…DCs-related gene signature (DCRGS) was constructed using integrated machine learning algorithms. Expression of key genes in clinical samples was examined by real-time q-PCR. …”
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Cetacean feeding modelling using machine learning: A case study of the Central-Eastern Mediterranean Sea by Carla Cherubini, Giulia Cipriano, Leonardo Saccotelli, Giovanni Dimauro, Giovanni Coppini, Roberto Carlucci, Carmelo Fanizza, Rosalia Maglietta

“…Risso's dolphin resulted to be the best modelled species, with the bio-chemical model based on the RUSBoost algorithm achieving a Balanced Classification Rate (BCR) of 94 %, primarily influenced by 3D chlorophyll-a concentrations, a close proxy for prey availability. …”
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Preoperative prediction of pituitary neuroendocrine tumor invasion using multiparametric MRI radiomics by Qiuyuan Yang, Tengfei Ke, Jialei Wu, Yubo Wang, Jiageng Li, Yimin He, Jianxian Yang, Nan Xu, Bin Yang

“…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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Inhibition of tumour necrosis factor alpha by Etanercept attenuates Shiga toxin-induced brain pathology by Robin Christ, Devon Siemes, Shuo Zhao, Lars Widera, Philippa Spangenberg, Julia Lill, Stephanie Thiebes, Jenny Bottek, Lars Borgards, Andreia G. Pinho, Nuno A. Silva, Susana Monteiro, Selina K. Jorch, Matthias Gunzer, Bente Siebels, Hannah Voss, Hartmut Schlüter, Olga Shevchuk, Jianxu Chen, Daniel R. Engel

“…Analysis of microglial populations using a novel human-in-the-loop deep learning algorithm for the segmentation of microscopic imaging data indicated specific morphological changes, which were reduced to healthy condition after inhibition of TNF-α. …”
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Ultrasonic and Microwave-assisted Solid-Liquid Extraction of Ginkgo biloba Phenolics: Study about Mass Transfer and PID Control by Chi XU, Hebin XU, Rui ZHU, Jing LI, Dandan LI, Yongbin HAN, Yi ZHENG, Yang TAO

“…Furthermore, fuzzy-PID controllers optimized by genetic algorithms or particle swarm optimization (PSO) algorithms outperformed traditional PID controller and individual fuzzy-PID controller to control the extraction process, achieving faster convergence with minimal overshoot. …”
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Integrative Bioinformatics Analysis of Pyroptosis-Related Genes and Analysis of Immune Cell Infiltration in Infantile Hemangioma Regression by Liu L, Lin S, Bai J, Zhang B

“…Additionally, a single-sample GSEA algorithm was applied to assess immune cell infiltration in IHs, and correlation analysis was performed between the hub-IH-PRGs and infiltrating immune cells.Results: Fourteen IH-PRGs were identified. …”
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OSBPL3 modulates the immunosuppressive microenvironment and predicts therapeutic outcomes in pancreatic cancer by Qihui Sun, Xiaoqi Zhu, Qi Zou, Yang Chen, Tingting Wen, Tingting Jiang, Xiaojia Li, Fang Wei, Keping Xie, Jia Liu

“…Notably, the “rf” algorithm model showed an AUC of 1 in the training set and AUCs of 0.887 and 0.977 in two validation datasets. …”
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Classification of Cigarette Types Using Computer Vision: An Analysis of Smoke Aggregation Features by Shishuan Guan, Lei Jiao, Zengyu Wang, Xiaofei Ji, Hongwei Zheng, Cunfeng Yu, Hongtao Li, Liwen Zheng, Shuaishuai Sun, Qiang Sun, Jun Li, Guangwei Jiang, Kezhi Wu, Erge Lin, Xinlong Zhang

“…Based on this data set, we applied the traditional vision algorithm to extract the diffusion width, sedimentation concentration and diffusion distance of smoke, and used the KNN model for training, and initially reached an accuracy of 69.8%. …”
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DYSSS: A Dynamic and Context-Aware Security System for Shared Sensor Networks by Claudio M. de Farias, Luci Pirmez, Luiz F. R. C. Carmo, Davidson Boccardo, Flávia C. Delicato, Igor L. dos Santos, Renato Pinheiro, Rafael O. Costa

“…Its basic feature is the nodes neighborhood monitoring and collaboration (through the use of the Byzantine algorithm) to identify an attack and enhance security. …”
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A new and automated risk prediction of coronary artery disease using clinical endpoints and medical imaging-derived patient-specific insights: protocol for the retrospective GeoCAD... by Louisa Jorm, Daniel Moses, Dona Adikari, Ramtin Gharleghi, Shisheng Zhang, Arcot Sowmya, Sze-Yuan Ooi, Susann Beier

“…The objectives are to (1) profile CTCA images with respect to variations in anatomical shape and associated haemodynamic risk expressing, at least in part, an individual’s CAD risk, (2) develop a machine-learning algorithm for the rapid assessment of anatomical risk directly from unprocessed CTCA images and (3) to build a novel CAD risk model combining traditional risk factors with these novel anatomical biomarkers to provide a higher accuracy CAD risk prediction tool.Ethics and dissemination The study protocol has been approved by the St Vincent’s Hospital Human Research Ethics Committee, Sydney—2020/ETH02127 and the NSW Population and Health Service Research Ethics Committee—2021/ETH00990. …”
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Oncolytic Viruses and Immunotherapy for the Treatment of Uveal Melanoma and Retinoblastoma: The Current Landscape and Novel Advances by Merve Kulbay, Nicolas Tuli, Massimo Mazza, Armaan Jaffer, Sarinee Juntipwong, Emily Marcotte, Stuti Misty Tanya, Anne Xuan-Lan Nguyen, Miguel N. Burnier, Hakan Demirci

“…., AU011), oncolytic viruses for metastatic UM, and targeted immunotherapies have shown great results in clinical trials for the future clinical application of these novel technologies in the treatment algorithm of certain intraocular tumors.…”
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CECT-Based Radiomic Nomogram of Different Machine Learning Models for Differentiating Malignant and Benign Solid-Containing Renal Masses by Qian L, Fu B, He H, Liu S, Lu R

“…Four mainstream machine learning algorithm training models, namely, support vector machine (SVM), k-nearest neighbour (kNN), light gradient boosting (LightGBM) and logistic regression (LR), were constructed to determine the best classifier model. …”
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A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model by Kun Yang, Xiaohua Sun, Ruofan Li, Zhenxue He, Xinxin Wang, Chao Wang, Bin Wang, Fushun Wang, Hongquan Liu

“…Image detection performance and seedling information were analyzed considering various dates, heights, and resolutions, and the K-means algorithm was utilized to cluster feature points and extract row information. …”
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Construction and Comparison of Machine Learning-Based Risk Prediction Models for Major Adverse Cardiovascular Events in Perimenopausal Women by Chen A, Chang X, Bian X, Zhang F, Ma S, Chen X

“…In the training set, Random Forest (RF) algorithm, backpropagation neural network (BPNN) and Logistic Regression (LR) were used to construct a MACE risk prediction model for perimenopausal women, and the test set was used to verify the model. …”
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A prediction model of liver fat fraction and presence of non-alcoholic fatty liver disease (NAFLD) among patients with overweight or obesity by Jie Chen, Jiang Yue, Jingjing Fu, Shengyun He, Qianjing Liu, Minglan Yang, Wang Zhang, Hua Xu, Qing Lu, Jing Ma

“…Through univariate analysis, we have identified potential factors, and the definitive elements in the prediction model were selected utilizing the forward stepwise regression algorithm. The Shang Hai Steatosis Index (SHSI) incorporates alanine aminotransferase (ALT), aspartate aminotransferase (AST), fasting insulin, and 1-h postload glycaemic levels, thereby furnishing the capability to predict NAFLD with an area under the receiver operator characteristic (AUROC) of 0.87. …”
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Fruit Detection and Yield Mass Estimation from a UAV Based RGB Dense Cloud for an Apple Orchard by Marius Hobart, Michael Pflanz, Nikos Tsoulias, Cornelia Weltzien, Mia Kopetzky, Michael Schirrmann

“…Ripe apples were detected by their color and structure from a photogrammetrically created three-dimensional point cloud with an automatic algorithm. The detection included the position, number, volume and mass of apples for all blocks over the orchard. …”
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High-resolution mapping of evapotranspiration over heterogeneous cropland affected by soil salinity by Meihan Liu, Huimin Lei, Xingwang Wang, Paula Paredes

“…Using a spatiotemporal image fusion algorithm implemented on the Google Earth Engine (GEE) platform, daily NDVI and LST datasets with a 30 m resolution were generated by fusing Landsat 8 and MODIS satellite data. …”
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Identification of Nicotinic Acetylcholine Receptor for N‐Acetylcysteine to Rescue Nicotine‐induced Injury Using Beating Cilia in Primary Tissue Derived Airway Organoids by Yichao Zheng, Qinyong Tian, Haowei Yang, Yongde Cai, Jiaxin Zhang, Yifen Wu, Shuo Zhu, Zuocheng Qiu, Yimin Lin, Jiangquan Hong, Yi Zhang, David Dockrell, Shaohua Ma

“…The organoids display apical‐out and basal‐in polarity and are enriched in beating cilia, which are sensitive to smoking challenge and NAC treatment. An algorithm is developed to measure ciliary beating activity by analyzing the altered beating pattern of cilia in response to nicotine challenge and NAC treatment. …”
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