7 Result(s)
within
Keyuan Jiang
Computer Science
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Chapter and Conference Paper
An Object Model Based Repository for Biological Pathways Using XML Database Technology
With the availability of a growing collection of biological pathway datasets, there is an increasing need for an efficient repository with the powerful search capability to facility large scaled analyses of bi...
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Chapter and Conference Paper
Mining Twitter Data for Potential Drug Effects
Adverse drug reactions have become one of the top causes of deaths. For surveillance of adverse drug events, patients have gradually become involved in reporting their experiences with medications through the ...
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Chapter and Conference Paper
A Streaming Execution Method for Multi-services in Mobile Cloud Computing
Commercially available mobile devices with various kinds of hardware and software platforms have resulted in a huge amount of mobile services. This has a new challenge in designing multiple services that are c...
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Chapter and Conference Paper
Matching Algorithm of Composite Service Based on Indexing Mechanism in BPM
Service matching technology has promoted the development of Business Process Management (BPM). It’s significant for us to know how to retrieve a qualified service from a large number of candidate services in ...
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Chapter and Conference Paper
An Explainable Approach of Inferring Potential Medication Effects from Social Media Data
Understanding medication effects is an important activity in pharmacovigilance in which patients are the most important contributor. Social media, where users share their personal experiences of medication eff...
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Chapter and Conference Paper
Mining Medication-Effect Relations from Twitter Data Using Pre-trained Transformer Language Model
Pharmacovigilance aims to promote safe use of pharmaceutical products by continuously assessing the safety of marketed medications. Lately, an active area of this endeavor is to use social media such as Twitte...
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Chapter and Conference Paper
Few-Shot Learning for Identification of COVID-19 Symptoms Using Generative Pre-trained Transformer Language Models
Since the onset of the COVID-19 pandemic, social media users have shared their personal experiences related to the viral infection. Their posts contain rich information of symptoms that may provide useful hint...
