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Deep learning

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Full-Text Articles in Bioinformatics

Table-To-Text: Generating Descriptive Text For Scientific Tables From Randomized Controlled Trials, Qiang Wei May 2020

Table-To-Text: Generating Descriptive Text For Scientific Tables From Randomized Controlled Trials, Qiang Wei

Dissertations & Theses (Open Access)

Unprecedented amounts of data have been generated in the biomedical domain, and the bottleneck for biomedical research has shifted from data generation to data management, interpretation, and communication. Therefore, it is highly desirable to develop systems to assist in text generation from biomedical data, which will greatly improve the dissemination of scientific findings. However, very few studies have investigated issues of data-to-text generation in the biomedical domain. Here I present a systematic study for generating descriptive text from tables in randomized clinical trials (RCT) articles, which includes: (1) an information model for representing RCT tables; (2) annotated corpora containing pairs …


Vaxinsight: An Artificial Intelligence System To Access Large-Scale Public Perceptions Of Vaccination From Social Media, Jingcheng Du Dec 2019

Vaxinsight: An Artificial Intelligence System To Access Large-Scale Public Perceptions Of Vaccination From Social Media, Jingcheng Du

Dissertations & Theses (Open Access)

Vaccination is considered one of the greatest public health achievements of the 20th century. A high vaccination rate is required to reduce the prevalence and incidence of vaccine-preventable diseases. However, in the last two decades, there has been a significant and increasing number of people who refuse or delay getting vaccinated and who prohibit their children from receiving vaccinations. Importantly, under-vaccination is associated with infectious disease outbreaks. A good understanding of public perceptions regarding vaccinations is important if we are to develop effective vaccination promotion strategies. Traditional methods of research, such as surveys, suffer limitations that impede our understanding of …


Utilizing Temporal Information In The Ehr For Developing A Novel Continuous Prediction Model, Kang Lin Hsieh Aug 2019

Utilizing Temporal Information In The Ehr For Developing A Novel Continuous Prediction Model, Kang Lin Hsieh

Dissertations & Theses (Open Access)

Type 2 diabetes mellitus (T2DM) is a nation-wide prevalent chronic condition, which includes direct and indirect healthcare costs. T2DM, however, is a preventable chronic condition based on previous clinical research. Many prediction models were based on the risk factors identified by clinical trials. One of the major tasks of the T2DM prediction models is to estimate the risks for further testing by HbA1c or fasting plasma glucose to determine whether the patient has or does not have T2DM because nation-wide screening is not cost-effective.

Those models had substantial limitations on data quality, such as missing values. In this dissertation, I …