July 25, 2023
Data Science Innovation to Advance Journalism
COLUMBIA, Mo. (July 24, 2023) — Damon Kiesow is now the Knight Chair in Journalism Innovation at the Missouri School of Journalism, an update from his previous title of Knight Chair in Digital Editing and Producing. The new title reflects the evolution of the endowed chair position and Kiesow’s research and service as he finishes his fifth year at the School. Read more…
July 24, 2023
Productive Summer Curriculum Retreat at the MU Institute for Data Science and Informatics
The faculty members at the MU Institute for Data Science and Informatics recently concluded a highly successful curriculum retreat this summer. The primary focus of the retreat was to meticulously review the curriculum, spanning from bootcamps to capstone projects, with the ultimate goal of providing an unparalleled learning experience for our students. Throughout the retreat, our dedicated faculty engaged in rigorous discussions and collaborative sessions to ensure the continuous refinement of our curriculum. By doing so, we aim to maintain the utmost coherence in our courses, while simultaneously delivering cutting-edge AI/ML tools and techniques in our data science training. This…
July 21, 2023
Deer spread COVID to humans multiple times, new research suggests
Americans have transmitted COVID-19 to wild deer hundreds of times, an analysis of thousands of samples collected from the animals suggests, and people have also caught and spread mutated variants from deer at least three times. The analysis published Monday stems from the first year of a multiyear federal effort to study the virus as it has spread into American wildlife, spearheaded by the U.S. Department of Agriculture’s Animal and Plant Health Inspection Service, or APHIS. Read More……
May 4, 2023
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…
April 25, 2023
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…
April 25, 2023
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…
April 9, 2023
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…
April 9, 2023
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,…
March 30, 2023
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.