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Pneumonia Detection on Chest X-ray using Radiomic Features and Contrastive Learning
Chest X-ray becomes one of the most common medical diagnoses due to its ...
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Contrastive Learning Improves Critical Event Prediction in COVID-19 Patients
Machine Learning (ML) models typically require large-scale, balanced tra...
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Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records
Computational prediction of in-hospital mortality in the setting of an i...
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Understanding Team Collaboration in Artificial Intelligence from the perspective of Geographic Distance
This paper analyzes team collaboration in the field of Artificial Intell...
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Biomedical Knowledge Graph Refinement and Completion using Graph Representation Learning and Top-K Similarity Measure
Knowledge Graphs have been one of the fundamental methods for integratin...
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Using Radiomics as Prior Knowledge for Abnormality Classification and Localization in Chest X-rays
Chest X-rays become one of the most common medical diagnoses due to its ...
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Can pandemics transform scientific novelty? Evidence from COVID-19
Scientific novelty is important during the pandemic due to its critical ...
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The Pace of Artificial Intelligence Innovations: Speed, Talent, and Trial-and-Error
Innovations in artificial intelligence (AI) are occurring at speeds fast...
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Coronavirus Knowledge Graph: A Case Study
The emergence of the novel COVID-19 pandemic has had a significant impac...
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Analysis of misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements
COVID-19 resulted in an infodemic, which could erode public trust, imped...
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Building a PubMed knowledge graph
PubMed is an essential resource for the medical domain, but useful conce...
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Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN
We present a multi-filtering Graph Convolution Neural Network (GCN) fram...
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A Simultaneous Inference Procedure to Identify Subgroups from RCTs with Survival Outcomes: Application to Analysis of AMD Progression Studies
With the uptake of targeted therapies, instead of the "one-fits-all" app...
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Co-contributorship Network and Division of Labor in Individual Scientific Collaborations
Collaborations are pervasive in current science. Collaborations have bee...
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Analyzing Linguistic Complexity and Scientific Impact
The number of publications and the number of citations received have bec...
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Gene-based Association Analysis for Bivariate Time-to-event Data through Functional Regression with Copula Models
Several gene-based association tests for time-to-event traits have been ...
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Copula-based semiparametric transformation model for bivariate data under general interval censoring
This research is motivated by discovering and underpinning genetic cause...
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Direct Citations between Citing Publications
This paper defines and explores the direct citations between citing publ...
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edge2vec: Learning Node Representation Using Edge Semantics
Representation learning for networks provides a new way to mine graphs. ...
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Examining Scientific Writing Styles from the Perspective of Linguistic Complexity
Publishing articles in high-impact English journals is difficult for sch...
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Aspect-Aware Latent Factor Model: Rating Prediction with Ratings and Reviews
Although latent factor models (e.g., matrix factorization) achieve good ...
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DIMM-SC: A Dirichlet mixture model for clustering droplet-based single cell transcriptomic data
Motivation: Single cell transcriptome sequencing (scRNA-Seq) has become ...
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Meta Path-Based Collective Classification in Heterogeneous Information Networks
Collective classification has been intensively studied due to its impact...
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General Scaled Support Vector Machines
Support Vector Machines (SVMs) are popular tools for data mining tasks s...
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