Results 21 to 30 of about 932,353 (284)
Anaerobe-enriched gut microbiota predicts pro-inflammatory responses in pulmonary tuberculosis
EBioMedicine, 2021 Background: The relationship between tuberculosis (TB), one of the leading infectious causes of death worldwide, and the microbiome, which is critical for health, is poorly understood.
Charissa C. Naidoo +18 more
doaj +1 more source
Texture features based microscopic image classification of liver cellular granuloma using artificial neural networks [PDF]
, 2019 Automated classification of Schistosoma mansoni granulomatous microscopic images of mice liver using Artificial Intelligence (AI) technologies is a key issue for accurate diagnosis and treatment.
Chen, Gaoxiang +6 more
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Empirical Co-occurrence Rate Networks for Sequence Labeling [PDF]
2013 12th International Conference on Machine Learning and Applications, 2013 Structured prediction has wide applications in many areas. Powerful and popular models for structured prediction have been developed. Despite the successes, they suffer from some known problems: (i) Hidden Markov models are generative models which suffer from the mismatch problem.
Zhu, Zhemin +3 more
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Semantic Concept Co-Occurrence Patterns for Image Annotation and Retrieval. [PDF]
, 2016 Describing visual image contents by semantic concepts is an effective and straightforward way to facilitate various high level applications. Inferring semantic concepts from low-level pictorial feature analysis is challenging due to the semantic gap ...
Bhanu, Bir, Feng, Linan
core +1 more source
Measuring similarity in co-occurrence data using ego-networks [PDF]
Chaos: An Interdisciplinary Journal of Nonlinear Science, 2020 The co-occurrence association is widely observed in many empirical data. Mining the information in co-occurrence data is essential for advancing our understanding of systems such as social networks, ecosystems, and brain networks. Measuring similarity of entities is one of the important tasks, which can usually be achieved using a network-based ...
Xiaomeng Wang, Yijun Ran, Tao Jia
openaire +3 more sources
Structure of a Media Co-occurrence Network [PDF]
, 2016 Social networks have been of much interest in recent years. We here focus on a network structure derived from co-occurrences of people in traditional newspaper media. We find three clear deviations from what can be expected in a random graph. First, the average degree in the empirical network is much lower than expected, and the average weight of a ...
Traag, Vincent +2 more
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Difficulty in inferring microbial community structure based on co-occurrence network approaches
BMC Bioinformatics, 2019 Background Co-occurrence networks—ecological associations between sampled populations of microbial communities inferred from taxonomic composition data obtained from high-throughput sequencing techniques—are widely used in microbial ecology.
Hokuto Hirano, Kazuhiro Takemoto
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Co-occurrence network of TV advertisements revealing Japanese lifestyle
Applied Network Science, 2021 The relationship between culture and the appeals in TV advertisements has been extensively studied. We attempted to reveal the image structure produced by TV commercials in Japan, which may show the cultural features of the country, and to evaluate its ...
Mariko I. Ito, Takaaki Ohnishi
doaj +1 more source
Inferring microbial co-occurrence networks from amplicon data: a systematic evaluation
mSystems, 2023 Microbes commonly organize into communities consisting of hundreds of species involved in complex interactions with each other. 16S ribosomal RNA (16S rRNA) amplicon profiling provides snapshots that reveal the phylogenies and abundance profiles of these
Dileep Kishore +5 more
doaj +1 more source
Fluctuations between high- and low-modularity topology in time-resolved functional connectivity [PDF]
, 2017 Modularity is an important topological attribute for functional brain networks. Recent studies have reported that modularity of functional networks varies not only across individuals being related to demographics and cognitive performance, but also ...
Betzel, Richard F. +6 more
core +2 more sources