March 17, 2023
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…
March 8, 2023
Developing a Web-based Interface of Sensor Technologies for Interventionists
The widespread adoption and growth of the consumer sensor technologies, including wearable and in-home sensors, present an opportunity for ambient monitoring of activities of daily living (ADLs) for health and behavioral intervention. Yet no open-source systems exist to incorporate disparate sensor technologies for health care professionals and researchers to monitor client/patient ADLs and assist individuals with health and wellness goals. The purpose of this study is to design and develop a data interface, using a user-centered co-design approach, for health care professionals. Informatics and design researchers engage with nurses, occupational therapists, and social workers to create a user-friendly and web-based…
March 8, 2023
Artificial Intelligence in Disease Prediction using Real World Health Data: Trends, Challenges, and The Future
Recent years have seen significant progress in using artificial intelligence (AI) to develop disease prediction models, which have the potential to improve diagnosis precision, enable early disease prevention, streamline clinical decision making, and reduce healthcare costs. This progress has been supported by the availability of large and diverse biomedical data, including Electronic Health Records (EHRs), which have become a valuable resource for disease prediction. The wide adoption of structured EHR systems has enabled historical patient records to serve as one of the most valuable resources for disease prediction. Traditional research for building disease prediction models relied on experts’ ability to…
Feb. 8, 2023
Rural populations facilitate early SARS-CoV-2 evolution and transmission
In the United States, rural populations comprise 60 million individuals and suffer from high COVID-19 disease burdens. Despite this, surveillance efforts are biased toward urban centers. Consequently, how rurally circulating SARS-CoV-2 viruses contribute toward emerging variants remains unknown. In this study, 544 urban and 435 rural COVID-19-positive respiratory specimens were collected from two healthcare systems in Missouri between July and December 2020, prior to COVID-19 vaccines. We saw high genetic diversity with 14 of 53 SARS-CoV-2 Pango lineages detected only in rural samples. The lineage diversity of SARS-CoV-2 in rural communities gradually increased whereas those in urban areas remained similar during…
Feb. 8, 2023
Exploration of Obesity and Multimorbidity at a Single Academic Institution.
In the US, overweight and obese adults account for more than two-thirds of the total population. Obesity has been established as a risk factor in many chronic conditions; and chronic conditions account for seven out of the top 10 leading causes of death and disability in the US. Multimorbidity occurs when a patient has two or more chronic conditions at the same time (without a single predominant condition). Research has established obesity as a risk factor for many chronic conditions; however, little is known about the co-occurrence of these conditions and the role that obesity plays. This ongoing research is…
Feb. 1, 2023
IDSI PhD student Will Baskett crunched EHR data, finding only a few long-haul symptoms directly related to COVID in comparison to generic viral infection
In a new study, a team of University of Missouri researchers made an unexpected discovery: people experiencing long-lasting effects from COVID-19 — known as “long COVID” or post-COVID conditions — are susceptible to developing only seven health symptoms for up to a year following the infection. They are: fast-beating heart, hair loss, fatigue, chest pain, shortness of breath, joint pain and obesity. Read More…
Feb. 1, 2023
Two IDSI Core Faculty Elected as Fellow of AAAS
Dr. Xiu-Feng “Henry” Wan and Dr. Xiaoqin Zou were named as Fellows of the American Association for the Advancement of Science. Read More…
Jan. 20, 2023
Identification of Spatially Variable Genes
Invasive species pose a unique threat to native species and habitat through direct and indirect competition of resources. Management of invasive species depends on precise identification of their current range and knowledge of how they spread. This project will utilize Plantescope Satellite Imagery to identify the presence of Callery Pear, an invasive ornamental tree species in Missouri. The unique phenology of the Callery Pear should allow for precise identification through Random Forest classification of the imagery. After identification, a logistic model will be built to predict the presence or absence of Callery Pear in the landscape based on a variety…
Jan. 20, 2023
Modeling Pyrus calleryana spread in central Missouri using remote sensing and a non-parametric modeling approach
Invasive species pose a unique threat to native species and habitat through direct and indirect competition of resources. Management of invasive species depends on precise identification of their current range and knowledge of how they spread. This project will utilize Plantescope Satellite Imagery to identify the presence of Callery Pear, an invasive ornamental tree species in Missouri. The unique phenology of the Callery Pear should allow for precise identification through Random Forest classification of the imagery. After identification, a logistic model will be built to predict the presence or absence of Callery Pear in the landscape based on a variety…