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  1. 1081
    “…We performed the latent Dirichlet allocation (LDA) algorithm for topic modeling and carried out a sentiment analysis. …”
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    Vaping discussion in the COVID-19 pandemic: An observational study using Twitter data
  2. 1082
    “…Un-weighted Unifrac also demonstrated that the probable group had a higher beta diversity than both the healthy and the confirmed group. A Dirichlet-multinomial mixture (DMM) model-based clustering method partitioned the tonsil microbiota into two distinct community types that did not correspond with disease status. …”
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    Compositional analysis of the tonsil microbiota in relationship to Streptococcus suis disease in nursery pigs in Ontario
  3. 1083
    “…METHODS: Data were collected from the patient medication reviews of sildenafil and tadalafil posted on WebMD and Ask a Patient. The latent Dirichlet allocation method of natural language processing was used to identify 5 distinctive topics from the patient medication reviews on each drug. …”
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    Comparison of the Erectile Dysfunction Drugs Sildenafil and Tadalafil Using Patient Medication Reviews: Topic Modeling Study
  4. 1084
    “…We used a machine learning tool, latent Dirichlet allocation, to identify 100 topics or themes within these reviews and used Pearson r to identify statistically significant correlations between topics and high (5-star) and low (1-star) ratings. …”
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    Patient Experience and Satisfaction in Online Reviews of Obstetric Care: Observational Study
  5. 1085
    “…On sentiment analysis, negative sentiment overwhelmed positive sentiment, and fear was the dominant emotion across the period. For the latent Dirichlet allocation model on tweets with fear emotion, the two topics were identified as “infect” and “vaccine confidence.” …”
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    The Effect of Fear of Infection and Sufficient Vaccine Reservation Information on Rapid COVID-19 Vaccination in Japan: Evidence From a Retrospective Twitter Analysis
  6. 1086
    “…NeRiT adopts the flexible Bayesian Dirichlet process regression to obtain the gene expression prediction weights in the first stage, uses pointwise mutual information to represent the general between-node correlation in the second stage and can effectively take the network structure among different gene nodes into account. …”
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    Network regression analysis in transcriptome-wide association studies
  7. 1087
    “…RESULTS: A mixed methods approach, including topic modeling using latent Dirichlet allocation, identified the top topics from the corpus to understand how Twitter users engage with discussions on work-related sentiments. …”
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    Thinking Aloud or Screaming Inside: Exploratory Study of Sentiment Around Work
  8. 1088
    “…Finally, we used the latent Dirichlet allocation algorithm to determine relevant high-risk COVID-19 themes. …”
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    Emotional Analysis of Tweets About Clinically Extremely Vulnerable COVID-19 Groups
  9. 1089
    “…METHODS: We defined 2 latent Dirichlet allocation (LDA) topic models using a novel data-driven and a more commonly used interpretability-based topic number selection approaches. …”
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    Text Topics and Treatment Response in Internet-Delivered Cognitive Behavioral Therapy for Generalized Anxiety Disorder: Text Mining Study
  10. 1090
    “…Textual data were clustered about their topical content using Latent Dirichlet Allocation (LDA), and speech cohesion between these addresses was examined using a similarity matrix and heatmap. …”
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    Qualitative content analysis of Nigerian heads-of-state and presidents’ inaugural addresses: text mining, topic modelling and sentiment analysis
  11. 1091
    “…METHODS: Text data were collected, including 55,612 PORs of 3430 doctors from three popular PRWs in the United States (RateMDs, HealthGrades, and Vitals) from March 01 to June 27, 2020. An improved latent Dirichlet allocation (LDA)-based topic modeling (topic coherence-based LDA [TCLDA]), manual annotation, and sentiment analysis tool were applied to extract a suitable number of topics, generate corresponding keywords, assign topic names, and determine trends in the extracted topics and specific emotions. …”
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    Mining topic and sentiment dynamics in physician rating websites during the early wave of the COVID-19 pandemic: Machine learning approach
  12. 1092
    “…The main topics of the papers were extracted through the Latent Dirichlet Allocation algorithm. Finally, temporal analysis was used to explore trends in the evolution of themes and health belief structures in the papers. …”
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    COVID-19 Vaccine–Related Information on the WeChat Public Platform: Topic Modeling and Content Analysis
  13. 1093
    por Li, Xiaosong, Ding, Wei, Zhang, Hong
    Publicado 2023
    “…The R package “Bibliometrix,” VOSviewer, CiteSpace, meta, and latent Dirichlet allocation (LDA) in Python were used to generate bibliometric and meta-analytical results. …”
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    Cinacalcet use in secondary hyperparathyroidism: a machine learning-based systematic review
  14. 1094
    “…In complete cases (n = 765 [97.6%]), we fitted linear, beta, and Dirichlet regression models to estimate cross-sectional differences in iAs%, MMA%, DMA%, PMI, and SMI per IQR-unit difference in each anthropometric measure, adjusting for drinking water arsenic, age, gestational age, education, living standards index, and plasma folate, vitamin B12, and homocysteine. …”
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    Anthropometric measures and arsenic methylation among pregnant women in rural northern Bangladesh
  15. 1095
    “…Additionally, [Formula: see text] -ep integrates the generation of myocardial fibers based on Laplace–Dirichlet Rule-Based Methods, previously released in Africa et al., 2023, within [Formula: see text] -fiber. …”
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    lifex-ep: a robust and efficient software for cardiac electrophysiology simulations
  16. 1096
    “…Based on the latent Dirichlet allocation algorithm we identified 25 topics that represent different diagnoses. …”
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    Towards a practical use of text mining approaches in electrodiagnostic data
  17. 1097
    “…METHODS: We collected data from Reddit (27,638 e-cigarette flavor-related posts from January 1, 2011, to June 30, 2015), JuiceDB (14,433 e-juice reviews from June 26, 2013 to November 12, 2015), and Twitter (13,356 “e-cig ban”-related tweets from January, 1, 2010 to June 30, 2015). Latent Dirichlet Allocation, a generative model for topic modeling, was used to analyze the topics from these data. …”
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    Identifying Topics for E-Cigarette User-Generated Contents: A Case Study From Multiple Social Media Platforms
  18. 1098
    “…We developed a new model using a Dirichlet process prior for splitting individuals into groups, with a Bayesian Lasso model in each group to link behavioral features with mental illness. …”
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    Group-Personalized Regression Models for Predicting Mental Health Scores From Objective Mobile Phone Data Streams: Observational Study
  19. 1099
    “…To account for parameter uncertainty, probabilistic sensitivity analysis was employed through Gamma, Normal, and Dirichlet distributions. All utilities, costs, and transition probabilities were replaced by fitted distributions. …”
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    Cost-effectiveness of different treat-to-target strategies in rheumatoid arthritis: results from the DREAM registry
  20. 1100
    “…Data analysis was carried out using Wilcoxon rank-sum test to assess pairwise differences of SCFAs’ profiles, partial least squares-discriminate analysis (PLS-DA) to determine the status membership based on distinct SCFAs’ profiles, and Dirichlet regression to determine factors influencing concentration levels of SCFAs. …”
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    Evaluation and comparison of short chain fatty acids composition in gut diseases
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