Patient-Reported Quality of Life Before and After Total Knee Arthroplasty: A Multicenter Observational Study by Chang J, Fu M, Cao P, Ding C, Wang D

“…Sociodemographic characteristics were assessed using a General Information Questionnaire, disability using the Knee Injury and Osteoarthritis Outcome Score (KOOS-PS), resting pain using the visual analogue scale (Pain-VAS), and HRQoL using the European Quality of Life Five Dimension Five Level (EQ-5D-5L) scale. The growth mixture model was used to identify group heterogeneity in the developmental trajectories of KOOS-PS, Pain-VAS, and EQ5D5L. …”
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Ni2+ and Cu2+ complexes of N-(2,6-dichlorophenyl)-N-mesityl formamidine dithiocarbamate structural and functional properties as CYP3A4 potential substrates by Segun D. Oladipo, Sizwe J. Zamisa, Abosede A. Badeji, Murtala A. Ejalonibu, Adesola A. Adeleke, Isiaka A. Lawal, Amr Henni, Monsurat M. Lawal

“…The protein attains at least five conformational states in the three studied models using a Gaussian Mixture Model-based clustering and free energy prediction. …”
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Internet-Based Early Intervention to Prevent Posttraumatic Stress Disorder in Injury Patients: Randomized Controlled Trial by Mouthaan, Joanne, Sijbrandij, Marit, de Vries, Giel-Jan, Reitsma, Johannes B, van de Schoot, Rens, Goslings, J Carel, Luitse, Jan SK, Bakker, Fred C, Gersons, Berthold PR, Olff, Miranda

“…Post hoc analyses using latent growth mixture modeling showed a significant decrease in PTSD symptoms in a subgroup of patients with severe initial symptoms (n=20) (P<.001). …”
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Detection of movement onset using EMG signals for upper-limb exoskeletons in reaching tasks by Emilio Trigili, Lorenzo Grazi, Simona Crea, Alessandro Accogli, Jacopo Carpaneto, Silvestro Micera, Nicola Vitiello, Alessandro Panarese

“…A set of subject-independent time-domain EMG features was selected according to information theory and their probability distributions corresponding to rest and movement phases were modeled by means of a two-component Gaussian Mixture Model (GMM). The detection of movement onset by two types of detectors was tested: the first type based on features extracted from single muscles, whereas the second from multiple muscles. …”
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Trajectories and predictors of vicarious traumatization in Chinese college students during the COVID-19 pandemic: A longitudinal study by Hong Luo, Zhen Yu, Ju Li, Yujie Wang, Xiaopan Shi, Dan Luo, Jie Chen, Bing Xiang Yang

“…A link to an online survey created by Questionnaire Star (https://www.wjx.cn/) was sent to the students to collect data. The Growth mixture modeling (GMM) and multiple logistic regression were used to identify the trajectories of VT and predictors for the distinct trajectories.ResultsThe incidence of VT at each wave varied from 9.9% at wave 1, 4.0% at wave 2, to 2.6% at wave 3. …”
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Novel Feature-Extraction Methods for the Estimation of Above-Ground Biomass in Rice Crops by David Alejandro Jimenez-Sierra, Edgar Steven Correa, Hernán Darío Benítez-Restrepo, Francisco Carlos Calderon, Ivan Fernando Mondragon, Julian D. Colorado

“…The first method is called GFKuts, an approach that optimally labels the plot canopy based on a Gaussian mixture model, a Montecarlo-based K-means, and a guided image filtering for the extraction of canopy vegetation indices associated with biomass yield. …”
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Evaluation of diffusion weighted imaging for tumor delineation in head-and-neck radiotherapy by comparison with automatically segmented 18F-fluorodeoxyglucose positron emission tom... by Tim Schakel, Boris Peltenburg, Jan-Willem Dankbaar, Carlos E. Cardenas, Michalis Aristophanous, Chris H.J. Terhaard, Johannes M. Hoogduin, Marielle E.P. Philippens

“…Target delineation on DW-MRI was performed by three observers, while for PET a semi-automatic segmentation was performed using a Gaussian mixture model. For interobserver variation and intermodality variation, volumes, overlap metrics and Hausdorff distances were calculated from the delineations. …”
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Propagation and Separation of Downslope Gravity Currents over Rigid and Emergent Vegetation Patches in Linearly Stratified Environments by Ying-Tien Lin, Yi-Qi Ye, Dong-Rui Han, Yu-Jia Chiu

“…Large eddy simulation (combined with the mixture model) and laboratory experiment were used to investigate the impact of emergent and rigid vegetation on the dynamics of downslope gravity currents in stratified environments. …”
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Predicting Emotional States Using Behavioral Markers Derived From Passively Sensed Data: Data-Driven Machine Learning Approach by Sükei, Emese, Norbury, Agnes, Perez-Rodriguez, M Mercedes, Olmos, Pablo M, Artés, Antonio

“…These regularly sampled but frequently missing and heterogeneous time series were analyzed with the following probabilistic latent variable models for data averaging and feature extraction: mixture model (MM) and hidden Markov model (HMM). The extracted features were then combined with a classifier to predict emotional state. …”
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Identification of bundles and driving factors of ecosystem services at multiple scales in the eastern China region by Xufang Zhang, Rongqing Han, Shijie Yang, Yu Yang, Xiantao Tang, Weijuan Qu

“…Taking eastern China as the research area, with the help of a Gaussian mixture model, redundancy analysis and geographically weighted regression models, the spatiotemporal pattern evolution of ecosystem services from multiple scale perspectives were conducted, and the interrelationships between ecosystem services and the driving factors were explored. …”
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Addressing non-response data for standardized post-acute functional items by Chih -Ying Li, Hyunkyoung Kim, Brian Downer, Mi Jung Lee, Kenneth Ottenbacher, Yong-Fang Kuo

“…We applied four methods to generate imputed values for each non-response functional item of each patient: Monte Carlo Markov Chains multiple imputations (MCMC), Fully Conditional Specification multiple imputations (FCS), Pattern-mixture model (PMM) multiple imputations and the Centers for Medicare and Medicaid Services (CMS) approach. …”
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INCREASING ACCURACY OF CALCULATION OF THE PATTERN OF GAS TEMPERATURES AT THE EXIT FROM THE COMBUSTION CHAMBER OF A GTE BY THE THREE-DIMENSIONAL METHOD COMPUTER MODELING by Сергей Анатольевич Евсеев, Дмитрий Викторович Козел, Игорь Федорович Кравченко

“…The problem of numerical simulation of the gas flow with the combustion of atomized liquid fuel was solved (the equilibrium combustion model pdf was used along with the partially mixed mixture model) in the annular combustion chamber of a gas turbine engine. …”
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Differential relationships of stress and HIV disclosure by gender: a person centered longitudinal study by Chengbo Zeng, Shan Qiao, Xiaoming Li, Xueying Yang, Zhiyong Shen, Yuejiao Zhou

“…Participants were assessed on perceived stress, sociodemographic characteristics, and number of HIV disclosure targets at baseline, 6-month, and 12-month follow-ups. Growth mixture modeling was used to characterize disclosure levels based on the changes of disclosure target number. …”
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Automatic Processing of Chinese GF-1 Wide Field of View Images by Y. Zhang, Y. Wan, B. Wang, Y. Kang, J. Xiong

“…Firstly, the images are validated by a self-adaptive Gaussian mixture model based cloud detection method to confirm whether they are qualified and suitable to be involved into the automatic processing workflow. …”
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Short-term wind power forecasting and uncertainty analysis based on FCM–WOA–ELM–GMM by Bo Gu, Hao Hu, Jian Zhao, Hongtao Zhang, Xinyu Liu

“…To accurately calculate the forecasting error probability density distribution, the Gaussian mixture model (GMM) was applied and the wind power forecast confidence intervals under different climatic conditions and time scales were calculated. …”
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Progression patterns of range of motion progression after open release for post-traumatic elbow stiffness by Farhan Ahmad, BS, Luis Torres-Gonzales, BS, Nabil Mehta, MD, Mark S. Cohen, MD, Xavier Simcock, MD, Robert W. Wysocki, MD

“…Range of motion (ROM) data were collected at preoperative, intraoperative, and postoperative intervals of 2 weeks, 6 weeks, 3 months, and 6 months. Growth mixture modeling (GMM) and latent class growth analysis (LCGA) were performed to identify motion recovery trajectory groups, and Student's t-tests were performed to compare ROM data between intervals. …”
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Developmental trajectories of sleep problems from childhood to adolescence both predict and are predicted by emotional and behavioral problems by Biyao Wang, Corinna Isensee, Andreas Becker, Janice Wong, Peter R. Eastwood, Rae-Chi Huang, Kevin C. Runions, Richard M. Stewart, Thomas Meyer, L. Geza Brüni, Florian Daniel Zepf, Florian Daniel Zepf, Aribert Rothenberger

“…Anxiety/depression was the only baseline factor that predicted the longitudinal course of sleep problems from ages 5 to 14 years, with anxious and depressed participants showing faster decreasing patterns of sleep problems over time than those without anxiety or depression. Growth mixture modeling identified two classes of sleep problem trajectories: Normal Sleepers (89.4%) and Troubled Sleepers (10.6%). …”
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An investigation of what protective individual- and community-level factors are associated with life satisfaction in middle-aged and older family carers in Ireland by Christine A. McGarrigle, Mark Ward, Rose Anne Kenny, Rose Anne Kenny

“…Participants were asked if they cared for someone, their relationship to the recipient, and the number of hours per week that they provided care. We used growth mixture modeling to identify latent trajectories of satisfaction with life (SWL) before and after caring was initiated. …”
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An HMM-DNN-Based System for the Detection and Classification of Low-Frequency Acoustic Signals from Baleen Whales, Earthquakes, and Air Guns off Chile by Susannah J. Buchan, Miguel Duran, Constanza Rojas, Jorge Wuth, Rodrigo Mahu, Kathleen M. Stafford, Nestor Becerra Yoma

“…A model with Gaussian Mixtures Models and HMM (HMM-GMM) was trained to obtain an initial set of HMM target states. …”
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A novel pathway-based distance score enhances assessment of disease heterogeneity in gene expression by Xiting Yan, Anqi Liang, Jose Gomez, Lauren Cohn, Hongyu Zhao, Geoffrey L. Chupp

“…Results Pre-defined biological pathways were downloaded and genes in each pathway were used to cluster samples using the Gaussian mixture model. The clustering results across different pathways were then summarized to calculate the pathway-based distance score between samples. …”
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