A5057391353- Biomedical Text Mining and Ontologies
- Semantic Web and Ontologies
- Data-Driven Disease Surveillance
- Machine Learning in Healthcare
- Data Quality and Management
- Health disparities and outcomes
- Vaccine Coverage and Hesitancy
- Artificial Intelligence in Healthcare and Education
- Mobile Health and mHealth Applications
- Electronic Health Records Systems
- Misinformation and Its Impacts
- Artificial Intelligence in Healthcare
- Child Abuse and Trauma
- Service-Oriented Architecture and Web Services
- Ethics in Clinical Research
- COVID-19 epidemiological studies
- Health, Environment, Cognitive Aging
- Chronic Disease Management Strategies
- Health Literacy and Information Accessibility
- Healthcare cost, quality, practices
- Explainable Artificial Intelligence (XAI)
- Child and Adolescent Psychosocial and Emotional Development
- Public Health Policies and Education
- Food Security and Health in Diverse Populations
- COVID-19 diagnosis using AI
University of Tennessee Health Science Center
2016-2025
Oak Ridge National Laboratory
2016-2025
University of Tennessee at Knoxville
2017-2024
Le Bonheur Children's Hospital
2022
McGill University
2011-2016
University of California, Berkeley
2015-2016
McGill University Health Centre
2013-2014
Concordia University
2005-2010
The COVID-19 pandemic fueled one of the most rapid vaccine developments in history. However, misinformation spread through online social media often leads to negative sentiment and hesitancy. To investigate vaccine-related discussion media, we conducted a analysis Latent Dirichlet Allocation topic modeling on textual data collected from 13 Reddit communities focusing Dec 1, 2020, May 15, 2021. Data were aggregated analyzed by month detect changes any latent topics. Polarity suggested these...
Traditional Protein NMR Referencing workflow leads to “chicken-egg dilemma” vs. proposed automatic Bayesian Model Optimized Reference Correction approach
Patient monitoring is vital in all stages of care. We here report the development and validation ICU length stay mortality prediction models. The models will be used an intelligent patient module Intelligent Remote Monitoring (IRPM) framework that monitors health status patients, generates timely alerts, maneuver guidance, or reports when adverse medical conditions are predicted. utilized publicly available Medical Information Mart for Intensive Care (MIMIC) database to extract data adult...
Abstract With the advances in artificial intelligence (AI), data‐driven algorithms are becoming increasingly popular medical domain. However, due to nonlinear and complex behavior of many these algorithms, decision‐making by such is not trustworthy for clinicians considered a black‐box process. Hence, scientific community has introduced explainable (XAI) remedy problem. This systematic scoping review investigates application XAI breast cancer detection risk prediction. We conducted...
Background The emergence of the novel coronavirus (COVID-19) and necessary separation populations have led to an unprecedented number new social media users seeking information related pandemic. Currently, with estimated 4.5 billion worldwide, data offer opportunity for near real-time analysis large bodies text disease outbreaks vaccination. These analyses can be used by officials develop appropriate public health messaging, digital interventions, educational materials, policies. Objective...
The importance of social components health has been emphasized both in epidemiology and public health. This paper highlights the significant impact on outcomes a novel way. Introducing concept sociomarkers, which are measurable indicators conditions patient is embedded, we employed machine learning approach that uses biomarkers sociomarkers to identify asthma patients at risk hospital revisit after an initial visit with accuracy 66%. analysis performed over integrated dataset consisting...
The COVID-19 pandemic has introduced new opportunities for health communication, including an increase in the public use of online outlets health-related emotions. People have turned to social media networks share sentiments related impacts pandemic. In this paper we examine role messaging shared by Persons Public Eye (i.e. athletes, politicians, news personnel) determining overall discourse direction. We harvested approximately 13 million tweets ranging from 1 January 2020 March 2022....
Background: COVID-19 is impacting people worldwide and currently a leading cause of death in many countries. This study sought to redefine the Healthy People 2030 SDoH taxonomy accommodate pandemic. Furthermore, we aim provide blueprint implement prototype for Urban Population Health Observatory (UPHO), web-based platform that integrates classified group-level indicators individual- aggregate-level population health data. The process building UPHO involves collecting integrating data from...
Breast cancer is one of the most commonly diagnosed cancers among women in United States and pain common side effect breast its treatment. Yet, relationships between social determinants experience/intensity remain under-investigated. We examined associations both at individual level neighborhood to understand how conditions are associated with perception early stage patients.We conducted integrated statistical analysis 1,191 treated a large center Memphis, Tennessee. Combining electronic...
Digital health, including telemedicine, has increased access to abortion care. The convenience, flexibility of appointment times, and ensured privacy users may make services via telemedicine preferable. This scoping review systematically mapped studies conducted on their effectiveness acceptability for providers. All published papers included in the United States were considered. Articles searched PubMed, CINAHL, Google Scholar databases September 2022. findings synthesized narratively,...
Background Access to health care services is a critical determinant of population and well-being. Measuring spatial accessibility essential for understanding distribution addressing potential inequities. Objective In this study, we developed geoprocessing toolbox including Python script tools the ArcGIS Pro environment measure using both classic enhanced versions 2-step floating catchment area method. Methods Each our incorporated distance buffers travel time catchments calculate scores...
Breast cancer screening plays a pivotal role in early detection and subsequent effective management of the disease, impacting patient outcomes survival rates. This study aims to assess breast rates nationwide United States investigate impact social determinants health on these Data mammography at census tract level for 2018 2020 were collected from Behavioral Risk Factor Surveillance System. We developed large dataset health, comprising 13 variables 72337 tracts. Spatial analysis employing...
Early life experiences are crucial for health and well-being, influencing physical, emotional, social development throughout the lifespan. Recent research shows that Positive Childhood Experiences (PCEs), such as access to supportive environments relationships, can help mitigate effects of Adverse (ACEs). In this context, we argue digital AI technologies offer innovative solutions by enabling screening promotion PCEs through personalized interventions.
Trauma care coordination in the pediatric intensive unit (PICU), including personalization of resources based on social determinants health (SDoH), is challenging for already strained healthcare providers. Patient SDoH data collection inconsistent, fragmented, and lacks standardization during hospitalization, complicating resource allocation usability both patients We propose implementing AI tools to standardize enhance navigation providers after trauma hospitalization. will use RE-AIM...
In this paper, we investigate the relationships between dwelling conditions and pediatric asthma prevalence, merging multiple data sources to unpack disproportionate prevalence in Memphis, TN, USA. Using 32 097 encounter from a children's hospital, map patient distributions Memphis. Connecting these with 244 000 property quality census data, show that is disproportionately prevalent bad neighborhoods, even after controlling for ethnicity poverty level. Furthermore, neighborhood inequality...