Chen Liang

Chen Liang
University of South Carolina | USC

PhD

About

41
Publications
6,014
Reads
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177
Citations
Education
August 2012 - February 2017
University of Texas Health Science Center at Houston
Field of study
  • Biomedical Informatics

Publications

Publications (41)
Article
Full-text available
Introduction: The COVID-19 pandemic has affected communities of colour the hardest. Non-Hispanic black and Hispanic pregnant women appear to have disproportionate SARS-CoV-2 infection and death rates. Methods and analysis: We will use the socioecological framework and employ a concurrent triangulation, mixed-methods study design to achieve three...
Chapter
As Twitter emerged as an important data source for pharmacovigilance, heterogeneous data veracity becomes a major concern for extracted adverse drug reactions (ADRs). Our objective is to categorize different levels of data veracity and explore linguistic features of tweets and Twitter variables as they may be used for automatic screening high-verac...
Preprint
Full-text available
Objective: To develop a rule-based algorithm that detects temporal information of clinical events during pregnancy for women with COVID-19 by inferring gestational weeks and delivery dates from Electronic Health Records (EHR) from the National COVID Cohort Collaborate (N3C). Materials and Methods: The EHR are normalized by the Observational Medical...
Article
Full-text available
Disparities and their geospatial patterns exist in morbidity and mortality of COVID-19 patients. When it comes to the infection rate, there is a dearth of research with respect to the disparity structure, its geospatial characteristics, and the pre-infection determinants of risk (PIDRs). This work aimed to assess the temporal–geospatial association...
Preprint
Full-text available
Introduction: Disparities and their geospatial patterns exist in coronavirus disease 2019 (COVID-19) morbidity and mortality for people who are engaged with clinical care. However, studies centered on viral infection cases are scarce. It remains unclear with respect to the disparity structure, its geospatial characteristics, and the pre-infection d...
Article
Background The rapid growth of inherently complex and heterogeneous data in HIV/AIDS research underscores the importance of Big Data Science. Recently, there have been increasing uptakes of Big Data techniques in basic, clinical, and public health fields of HIV/AIDS research. However, no studies have systematically elaborated on the evolving applic...
Article
Objectives: Ending the HIV epidemic requires innovative use of data for intelligent decision-making from surveillance through treatment. This study sought to examine the usefulness of using linked integrated PLWH health data to predict PLWH's future HIV care status and compare the performance of machine-learning methods for predicting future HIV c...
Article
Literature suggests that federal funding allocation for HIV-related research in the US may not align with HIV disease burden but is influenced by structural disparities. This study sought to examine how federal funding allocation is associated with HIV disease burden and research capacity of states by applying Big Data integration, text mining, and...
Preprint
Full-text available
Social media analysis provides a new approach to monitoring and understanding risk perceptions regarding COVID-19 over time. Our current understandings of risk perceptions regarding COVID-19 do not disentangle the three dimensions of risk perceptions (perceived susceptibility, perceived severity, and negative emotion) over a long enough timeframe t...
Preprint
Full-text available
Background: The rapid growth of inherently complex and heterogeneous data in HIV/AIDS research underscores the importance of Big Data analytics. Recently, there have been increasing uptakes of Big Data techniques in basic, clinical, and public health fields of HIV/AIDS research. However, no studies have systematically elaborated on the evolving app...
Preprint
Full-text available
Adverse drug reactions (ADRs) lead to high disease burden and health expenditure. Aside from traditional data sources used for pharmacovigilance, social media have emerged as an important supplemental data source for monitoring patients and consumers reported ADRs. Recently, there have been increasing concerns about the data veracity of ADRs extrac...
Preprint
BACKGROUND Over the last decades, patient review websites (PRWs) have emerged as an important web-based platform for doctors’ ratings and reviews. Recent studies suggested the significance of PRWs as an information source 1) for patients to choose doctors, 2) for healthcare providers to learn and improve from patients’ feedbacks, and 3) to foster a...
Article
Full-text available
Background: Over the last two decades, patient review websites have emerged as an essential online platform for doctor ratings and reviews. Recent studies suggested the significance of such websites as a data source for patients to choose doctors for healthcare providers to learn and improve from patient feedback and to foster a culture of trust a...
Article
Full-text available
Background: Systems-centered root cause analysis (RCA) of patient safety events presents unique advantages as it aims to disclose vulnerabilities of healthcare systems. However, the increasing number of collected events poses the problems of low efficiency and information overload for traditional RCA. Objectives: This study aims to improve syste...
Article
Full-text available
Despite U.S. federal agencies increasing their investment since 1999's release of To Err Is Human, recent reports suggest there is a lack of measurable outcomes in patient safety research. The present study sought to explore the associations between federal incentives of patient safety research and the outcomes from 1995 to 2014, in which the two h...
Article
Full-text available
Background: The existing community-wide bodies of biomedical ontologies are known to contain quality and content problems. Past research has revealed various errors related to their semantics and logical structure. Automated tools may help to ease the ontology construction, maintenance, assessment and quality assurance processes. However, there ar...
Chapter
Safety and quality measurement of dental care is important but shows a lack of standardized measure concept set. In recent years, patient review websites (PRW) emerged as a widely used platform for health consumers, including dental patients. The massive patient online reviews (POR) are a rich data source that captures various aspects of safety and...
Chapter
Online Lesbian, Gay, Bisexual, and Transgender (LGBT) support communities have emerged as a major social media platform for sexual and gender minorities (SGM). These communities play a crucial role in providing LGBT individuals a private and safe space for networking because LGBT individuals are more likely to experience social isolation and family...
Article
Full-text available
Background The number of patient online reviews (PORs) has grown significantly, and PORs have played an increasingly important role in patients’ choice of health care providers. Objective The objective of our study was to systematically review studies on PORs, summarize the major findings and study characteristics, identify literature gaps, and ma...
Preprint
BACKGROUND The number of patient online reviews (PORs) have grown significantly and PORs have played an increasingly important role in patients’ choice of healthcare providers. OBJECTIVE To systematically review studies on PORs, summarize the major findings and study characteristics, identify literature gaps, and make recommendations for future re...
Article
Full-text available
Background: Healthcare services, particularly in patient-provider interaction, often involve highly emotional situations, and it is important for physicians to understand and respond to their patients' emotions to best ensure their well-being. Methods: In order to model the emotion domain, we have created the Visualized Emotion Ontology (VEO) to...
Poster
In order for machines to understand or express emotion to users, the specific emotions must be formally defined and the software coded to how those emotions are to be expressed. This is particularly important if devices or computer-based tools are utilized in clinical settings, which may be stressful for patients and where emotions can dominate the...
Article
Full-text available
With the maturation of the patient safety event reporting, key challenges emerged to explain why measurable outcomes in improving patient safety have been limited. One of the challenges is concerned with the relatively slow development of reporting, collecting, analysing narrative portion of the reports. The paper details how narratives construct t...
Article
Full-text available
Over the past two decades, there have seen an ever-increasing amount of patient safety reports yet the capacity of extracting useful information from the reports remains limited. Classification of patient safety reports is the first step of performing a downstream analysis. In practice, the manual review processes for classification are labor-inten...
Article
Full-text available
Patient falls are a common safety event type that impairs the healthcare quality. Strategies including solution tools and reporting systems for preventing patient falls have been developed and implemented in the U.S. However, the current strategies do not include timely knowledge support, which is in great need in bridging the gap between reporting...
Article
Full-text available
The identification of the severity of patient safety events promotes prioritized safety analysis and intervention. The Harm Scale developed by the Agency for Healthcare Research and Quality is widely used in the US hospitals. However, recent studies have indicated a moderate to poor inter-rater reliability of the Harm Scale across a number of US ho...
Article
Full-text available
Purpose: The current development of patient safety reporting systems is criticized for loss of information and low data quality due to the lack of a uniformed domain knowledge base and text processing functionality. To improve patient safety reporting, the present paper suggests an ontological representation of patient safety knowledge. Design/meth...
Article
Full-text available
Despite ongoing progress towards treating mental illness, there remain significant difficulties in selecting probable candidate drugs from the existing database. We describe an ontology - oriented approach aims to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. Along with this approach...
Conference Paper
Incident reporting enables clinicians to examine historical patient safety events and to target different levels of analysis toward actionable knowledge. The cross-cultural adaptation of reporting instruments promotes the international communication on medical errors and patient safety culture.This study initializes a translation and adaptation of...
Article
Full-text available
There remain significant difficulties selecting probable candidate drugs from existing databases. We describe an ontology-oriented approach to represent the nexus between genes, drugs, phenotypes, symptoms, and diseases from multiple information sources. We also report a case study in which we attempted to explore candidate drugs effective for bipo...
Article
Data quality was placed as a major reason for the low utility of patient safety event reporting systems. A pressing need in improving data quality has advanced recent research focus in data entry associated with human factors. The debate on structured data entry or unstructured data entry reveals not only a trade-off problem among data accuracy, co...
Article
Full-text available
Over the past decade, improving healthcare quality and safety through patient safety event reporting systems has drawn much attention. Unfortunately, such systems are suffering from low data quality, inefficient data entry and ineffective information retrieval. For improving the systems, we develop a semantic web ontology based on the WHO Internati...
Conference Paper
Patient safety reporting system is in an imperative need for reducing and learning from medical errors. Presently, a great number of the reporting systems are suffering low quality of data and poor system performance associated with data quality. For improving the quality of data and the system performance towards reducing harm in healthcare, we in...
Conference Paper
Full-text available
There has been a pressing need for improving patient safety. Sizable amount of Americans do not feel safe about health care, as it is supposed to be [1]. Meanwhile, preventable medical errors that harm patients cost $17.1 billion a year which over-burdened the healthcare system [2]. Although the reasons why errors happen can be complex due to the i...
Conference Paper
Full-text available
Research in the field of spatial cognition has advocated a frame of reference (FOR)-based cognitive representation system to account for human's spatial reasoning and navigation capacities. It has been argued that such mental models may also contribute to the underlying mechanisms of Theory of Mind (ToM). In the present study, we investigated how p...

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