Exploration of Geospatial Artificial Intelligence (AI) Using Remote Sensing to Discover Climate, Environment, and Anthropogenic Features Related to Population Health
Computational modeling of geospatial data can bring valuable insight into communicable diseases, noncommunicable diseases, and vector-borne diseases. However, each of these disease classes has its own challenges in terms of geospatial data analysis. Complex dynamics of environmental and social risk factors can determine the distribution of some diseases such as COVID-19, obesity and malaria, respectively. Environmental factors such as humidity, precipitation, rainfall, temperature, land use and land coverage, vegetation, and elevation play key roles in predicting prevalence or outbreaks. Measuring these features is time-consuming, costly, and biased since they are subject to human judgment. Remote sensing data, environmental and imagery,…
Exploring the Role of social media in Health Information Dissemination: A Focus on Vaccine Equity and Health Insurance
Social media has increasingly become a popular platform for sharing and seeking health information. However, the credibility and usefulness of this information are often questionable. The overall goal of my research program is to provide a comprehensive evaluation of chronic disease health information as well as other related topical health issues on social media channels and to explore the role of these channels in information dissemination using social network analysis. This presentation describes two studies on trending health topics during the COVID-19 pandemic. The first study aimed to evaluate health and vaccine equity trends during the Omicron wave on Twitter…
Tool Development for Resolving and Visualizing Heartbeats Measured by Cardiac Magnetic Resonance
Atrial fibrillation (AFib) is the most common irregularity of heartbeats. It can cause significant symptoms and impair heart function. Its irregular and often very rapid heart rhythm can lead to blood clots that cause stroke or heart attack, especially as the patient ages. The irregularity of heartbeats has prevented visualization of the heart using standard cardiac magnetic resonance (CMR), which usually attempts to average the beats. Real-time CMR imaging, without averaging, is better suited to visualizing irregular cardiac cycles. However, radiology lacks methods to manage the irregularity. We developed tools for easy viewing and comparison heterogeneous heartbeats measured by CMR…
Utilizing Real-World EHR Data: Early Predictive and Prescriptive Analysis for Glaucoma Using Machine Learning Methods
Electronic health records (EHRs) have emerged as a crucial source of data for data-driven translational clinical research. Meanwhile, machine learning (ML) models have advanced rapidly and are now a potent tool for analyzing EHR data, allowing us to harness a large amount of diverse clinical information. Various ML techniques have been created and adapted to predict outcomes using EHR data. However, effectively utilizing an observational and predictive window from the sequential EHR data is vital to developing a reliable model. This investigation applies advanced ML methods for predictive and prescriptive analysis, targeting multiple clinical encounters to provide suitable decision-making recommendations…
Development of AI Models for Remote Sensing City Livability Fitness
Tracking a city’s livability fitness is particularly important for the continued urbanization of civilization. Urban environmental and air quality and overall fitness are decreasing due to natural and anthropogenic events, causing degradation of living quality and leading to various population health issues, including heart and lung problems and even premature death. City fitness monitoring is mostly dependent on ground sensor deployment. However, this ground sensor-based monitoring is often not continuous and extensive due to the lack of resources and a very low number of ground observations. Another approach is to estimate city fitness parameters using models built with remote sensing…
FatPlants: A Comprehensive Website Platform of Plant Fat Related Genes, Proteins and Metabolism
Increasing seed oil content by plant breeding has resulted in trade-offs or penalties with respect to protein content, seed size, or seed set. The molecular basis for this impasse is mostly speculative. Use of current global profiling approaches to better understand both the metabolic consequences of higher oil and the basis for reduced yield must also deal with off-target genetic mutations (even in near-isogenic lines), ultimately confounding cause-effect interpretations. We propose a diverse, integrated strategy to study the consequences of higher lipid production by studying transgenic plants specifically engineered to produce higher seed oil. As a part of this collaborative project,…
Enhancing Health Equity of Aging-in-Place Older Adults with Sustainable Technology: Current Projects and Considerations to Data Science
We discuss the importance of sustainable technology in promoting health equity among aging-in-place older adults. We identify three key considerations necessary for the sustainability of technology in the health field, and examine ongoing projects that align with these considerations, including remote in-home sensor data and electronic health record integration to deliver tailored health messages to independent living older adults, and virtual reality simulations for nursing. Data science components (e.g., multimodal data integration, causal discovery analysis) to effectively support the health and well-being of older adults aging in place that pertains to these sustainable technology-driven projects will be discussed.
Uncovering CD137 Agonist’s Role in Cancer Immunoprotection via Interactive Multiomics Data Analytics and Visualization Portal
Anti-CD137 monoclonal antibody has been developed to improve anti-cancer immunity in several cancer models and are in clinical trials. SA-4-1BBL, a novel CD137 receptor agonist, has shown cancer immunoprevention in several tumor models as a single agent, yet an agonistic CD137 Ab (3H3) was ineffective in generating cancer prevention. The prevention mechanism by which SA-4-1BBL by which the innate immune system involve in the protection remains unknown. For understanding the mechanisms of action mouse models were treated with SA-4-1BBL and 3H3, samples were collected for performing single and bulk RNA-sequencing as well as flow Cytometry to get the cell counts.
A Semi-Supervised Approach to Unobtrusively Predict Abnormality in Breathing Patterns Using Hydraulic Bed Sensor Data in Older Adults Aging-in-place
Shortness of breath is often considered to be a repercussion of aging in older adults due, as such respiratory illnesses like COPD or respiratory illnesses due to heart-related issues are often misdiagnosed or under-diagnosed or ignored at early stages. Continuous health monitoring using ambient sensors has the potential to solve this problem for older adults at aging-in-place facilities. In this work, we leverage continuous respiratory health data collected by using ambient hydraulic bed sensors that were installed in the apartments of older adults in aging-in-place Americare facilities to find the data adaptive indicators related to shortness of breath. We used…