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  1. 1061
    “…METHODS: First, we applied a classic text mining technique, latent Dirichlet allocation (LDA), to detect the different topics discussed on social media dealing with breast cancer. …”
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    Online Artículo Texto
    What Patients Can Tell Us: Topic Analysis for Social Media on Breast Cancer
  2. 1062
    “…Finally, we extracted trending topics from each of these widely used drugs’ tweets using latent Dirichlet allocation (LDA). RESULTS: Our proposed classifier obtained an F(1) score of 0.82, which significantly outperformed the two benchmark classifiers (ie, P<.001 with the lexicon-based and P=.048 with the 1-gram term frequency [TF]). …”
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    Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data
  3. 1063
    “…Analyses were performed based on the Dirichlet-Multinomial distribution to compare group mean relative taxonomic abundances; Simpson and Shannon diversity indices were compared among groups longitudinally. …”
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    Successful Response to Microbiota-Based Drug RBX2660 in Patients with Recurrent Clostridium Difficile Infection is Associated with More Pronounced Alterations in Microbiome Profile
  4. 1064
    “…CRS patients clustered into two distinct microbial subgroups using probabilistic modelling Dirichlet (DC) multinomial mixtures. DC1 exhibited significantly reduced bacterial diversity and increased dispersion and was dominated by Pseudomonas, Haemophilus, and Achromobacter. …”
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    Comparison of Subtyping Approaches and the Underlying Drivers of Microbial Signatures for Chronic Rhinosinusitis
  5. 1065
    “…After completing natural language processing of the Korean language, a morphological analyzer, we performed topic modeling using latent Dirichlet allocation (LDA) in the Python library, Gensim. …”
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    Mining Hidden Knowledge About Illegal Compensation for Occupational Injury: Topic Model Approach
  6. 1066
    “…METHODS: The machine learning (ML) framework and Latent Dirichlet Allocation (LDA) topic modeling tool were used to collect and analyze behavioral data on EE. …”
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    Exploring Abnormal Behavior Patterns of Online Users With Emotional Eating Behavior: Topic Modeling Study
  7. 1067
    “…Term frequency–inverse document frequency, latent dirichlet allocation models, and naive Bayes were employed to mine the various topic categories. …”
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    Determining the Topic Evolution and Sentiment Polarity for Albinism in a Chinese Online Health Community: Machine Learning and Social Network Analysis
  8. 1068
    “…METHODS: This article was based on the Latent Dirichlet Allocation (LDA) topic model. From a third-party platform-based B2C online pharmacy and a proprietary B2C online pharmacy (JD Pharmacy and J1.COM, respectively), 136,630 pieces of over-the-counter (OTC) drug review data posted from January 1, 2015 to December 31, 2018 were selected as samples and used to explore the satisfaction factors of B2C online pharmacy consumers regarding the entire drug purchasing process. …”
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    Consumers’ satisfaction factors mining and sentiment analysis of B2C online pharmacy reviews
  9. 1069
    “…For the second approach, we elicited Dirichlet prior distributions by three clinical experts. …”
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    Using informative prior based on expert opinion in Bayesian estimation of the transition probability matrix in Markov modelling—an example from the cost-effectiveness analysis of the treatment of patients with predominantly negative symptoms of schizophrenia with cariprazine
  10. 1070
    “…We used a machine learning approach, Latent Dirichlet Allocation (LDA), to identify popular unigrams and bigrams, salient topics and themes, and sentiments in the collected tweets. …”
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    Twitter Discussions and Emotions About the COVID-19 Pandemic: Machine Learning Approach
  11. 1071
    por Stokes, Ian A., Lucas, Andrew J.
    Publicado 2021
    “…Using perturbation theory and the Green’s function for Laplace’s equation in 2D with Dirichlet boundary conditions, we obtain integrals for the horizontal and vertical components of the wave-induced wind in a frame of reference moving with the wave. …”
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    Wave-slope soaring of the brown pelican
  12. 1072
    por Borakati, Aditya
    Publicado 2021
    “…Qualitative data were analysed using text mining with most frequent words, sentiment analysis with the AFINN-111 and syuzhet lexicons and topic modelling using the Latent Dirichlet Allocation (LDA). RESULTS: One thousand six hundred and eleventh collaborators from 24 countries completed the e-learning course; 1396 (86.7%) were medical students; 1067 (66.2%) entered feedback. 1031 (96.6%) rated the quality of the course a 4/5 or higher (mean 4.56; SD 0.58). …”
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    Evaluation of an international medical E-learning course with natural language processing and machine learning
  13. 1073
    “…Following standard preprocessing steps, we use topic modeling with Latent Dirichlet allocation (LDA) to cluster the abstracts following a minimization algorithm. …”
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    5335 days of Implementation Science: using natural language processing to examine publication trends and topics
  14. 1074
    por Bersanelli, Matteo, Travaglino, Erica, Meggendorfer, Manja, Matteuzzi, Tommaso, Sala, Claudia, Mosca, Ettore, Chiereghin, Chiara, Di Nanni, Noemi, Gnocchi, Matteo, Zampini, Matteo, Rossi, Marianna, Maggioni, Giulia, Termanini, Alberto, Angelucci, Emanuele, Bernardi, Massimo, Borin, Lorenza, Bruno, Benedetto, Bonifazi, Francesca, Santini, Valeria, Bacigalupo, Andrea, Voso, Maria Teresa, Oliva, Esther, Riva, Marta, Ubezio, Marta, Morabito, Lucio, Campagna, Alessia, Saitta, Claudia, Savevski, Victor, Giampieri, Enrico, Remondini, Daniel, Passamonti, Francesco, Ciceri, Fabio, Bolli, Niccolò, Rambaldi, Alessandro, Kern, Wolfgang, Kordasti, Shahram, Sole, Francesc, Palomo, Laura, Sanz, Guillermo, Santoro, Armando, Platzbecker, Uwe, Fenaux, Pierre, Milanesi, Luciano, Haferlach, Torsten, Castellani, Gastone, Della Porta, Matteo G.
    Publicado 2021
    “…Using Bayesian networks and Dirichlet processes, we combined mutations in 47 genes with cytogenetic abnormalities to identify genetic associations and subgroups. …”
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    Classification and Personalized Prognostic Assessment on the Basis of Clinical and Genomic Features in Myelodysplastic Syndromes
  15. 1075
    “…Specifically, we analyzed tweets by visualizing high-frequency word clouds and correlations between word tokens. We built a latent Dirichlet allocation (LDA) topic model to identify commonly discussed topics in a large sample of tweets. …”
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    Tweet Topics and Sentiments Relating to COVID-19 Vaccination Among Australian Twitter Users: Machine Learning Analysis
  16. 1076
    “…To analyze these threads, we applied top-down and bottom-up language analysis methods based on topic modeling with latent Dirichlet allocation and 13 indicators from the Linguistic Inquiry and Word Count program, respectively. …”
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    Changes in Language Style and Topics in an Online Eating Disorder Community at the Beginning of the COVID-19 Pandemic: Observational Study
  17. 1077
    por Xiong, Ziyu, Li, Pin, Lyu, Hanjia, Luo, Jiebo
    Publicado 2021
    “…To better understand the public opinion, we used latent Dirichlet allocation to extract topics and investigate how tweet contents are related to people’s attitude. …”
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    Social Media Opinions on Working From Home in the United States During the COVID-19 Pandemic: Observational Study
  18. 1078
    por Liu, Siru, Li, Jili, Liu, Jialin
    Publicado 2021
    “…The main topics in tweets were extracted by latent Dirichlet allocation analysis. RESULTS: We collected 2,678,372 tweets related to COVID-19 vaccines from 841,978 unique users and annotated 5000 tweets. …”
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    Leveraging Transfer Learning to Analyze Opinions, Attitudes, and Behavioral Intentions Toward COVID-19 Vaccines: Social Media Content and Temporal Analysis
  19. 1079
    “…In this study, the Ortony, Clore, and Collins (OCC) model, Word2Vec, and Bi-directional Long Short-Term Memory model were employed to determine emotional types, train vectorization of words, and identify each text emotion for the training set. Latent Dirichlet Allocation models were also employed to mine the various topic categories, while topic emotional evolution was visualized. …”
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    Analysis of social media data for public emotion on the Wuhan lockdown event during the COVID-19 pandemic
  20. 1080
    “…Tweet content was analyzed for sentiment and topic, using Latent Dirichlet Allocation. We used social network analysis to examine the degree to which identified topics are siloed within specific groups or disseminated through the broader T1D web-based community. …”
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    Mapping Individual Differences on the Internet: Case Study of the Type 1 Diabetes Community
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