Results 51 to 60 of about 7,298 (159)
Personalized anti-tumor drug efficacy prediction based on clinical data
HeliyonAnti-tumor drug efficacy prediction poses an unprecedented challenge to realizing personalized medicine. This paper proposes to predict personalized anti-tumor drug efficacy based on clinical data.
Xinping Xie +7 more
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Using Topic Modeling Methods for Short-Text Data: A Comparative Analysis
Frontiers in Artificial Intelligence, 2020 With the growth of online social network platforms and applications, large amounts of textual user-generated content are created daily in the form of comments, reviews, and short-text messages.
Rania Albalawi +2 more
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Latent Dirichlet Allocation in Generative Adversarial Networks
CoRR, 2018 We study the problem of multimodal generative modelling of images based on generative adversarial networks (GANs). Despite the success of existing methods, they often ignore the underlying structure of vision data or its multimodal generation characteristics.
Lili Pan 0001 +4 more
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Latent Dirichlet Allocation for Automatic Document Categorization [PDF]
, 2009 In this paper we introduce and evaluate a technique for applying latent Dirichlet allocation to supervised semantic categorization of documents. In our setup, for every category an own collection of topics is assigned, and for a labeled training document only topics from its category are sampled.
István Bíró, Jácint Szabó
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Latent Beta-Liouville Probabilistic Modeling for Bursty Topic Discovery in Textual Data
Proceedings of the International Florida Artificial Intelligence Research Society ConferenceTopic modeling has become a fundamental technique for uncovering latent thematic structures within large collections of textual data. However, conventional models often struggle to capture the burstiness of topics.
Shadan Ghadimi +2 more
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Profiling heterogeneity of Alzheimer's disease using white-matter impairment factors
NeuroImage: Clinical, 2018 The clinical presentation of Alzheimer's disease (AD) is not unitary as heterogeneity exists in the disease's clinical and anatomical characteristics. MRI studies have revealed that heterogeneous gray matter atrophy patterns are associated with specific ...
Xiuchao Sui, Jagath C. Rajapakse
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Author Identification Using Latent Dirichlet Allocation
, 2018 We tackle the task of author identification at PAN 2015 through a Latent Dirichlet Allocation (LDA) model. By using this method, we take into account the vocabulary and context of words at the same time, and after a statistical process find to what extent the relations between words are given in each document; processing a set of documents by LDA ...
Hiram Calvo +2 more
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Analisis Sentimen Multi-Aspek terhadap Ulasan Pengguna Aplikasi M-Pajak Menggunakan Model IndoBERT
Techno.ComAplikasi M-Pajak menghadapi tantangan dalam evaluasi layanan akibat banyaknya ulasan tidak terstruktur. Penelitian ini bertujuan untuk menganalisis sentimen multi-aspek menggunakan model Deep Learning berbasis arsitektur IndoBERT yang dioptimalkan dengan
Hansen Utomo Gunawan +1 more
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Modeling Word Relatedness in Latent Dirichlet Allocation
CoRR, 2014 Standard LDA model suffers the problem that the topic assignment of each word is independent and word correlation hence is neglected. To address this problem, in this paper, we propose a model called Word Related Latent Dirichlet Allocation (WR-LDA) by incorporating word correlation into LDA topic models.
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Covid-19 Tweets Sentiment Analysis with Latent Dirichlet Allocation Topic Modeling
The Owl, 2022 Analysis of Covid-19 vaccine tweets has been an extensive focus in understanding user trends throughout the pandemic. This project concentrated on the development of a Latent Dirichlet Allocation (LDA) model along with sentiment analysis to better ...
Akhil Shiju
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