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Uncovering CD137 Agonist’s Role in Cancer Immunoprotection via Interactive Multiomics Data Analytics and Visualization Portal
Presenter:

Pallav Singh

Date:

03-23-2023

Time:

4:00 PM-4:30 PM

Location:

S203 Memorial Union

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

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A Semi-Supervised Approach to Unobtrusively Predict Abnormality in Breathing Patterns Using Hydraulic Bed Sensor Data in Older Adults Aging-in-place
Presenter:

Pallavi Gupta

Date:

03-23-2023

Time:

3:30PM-4:00PM

Location:

S203 Memorial Union

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

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Developing a Web-based Interface of Sensor Technologies for Interventionists
Presenter:

Katrina Boles

Date:

03-09-2023

Time:

4:00pm-4:30pm

Location:

S204 Memorial Union

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

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Artificial Intelligence in Disease Prediction using Real World Health Data: Trends, Challenges, and The Future
Presenter:

Q

Date:

03-09-2023

Time:

3:30pm-4:00pm

Location:

S204 Memorial Union

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),

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Rural populations facilitate early SARS-CoV-2 evolution and transmission 
Presenter:

Cynthia Tang

Date:

02-09-2023

Time:

4:00PM-4:30PM

Location:

S203 Memorial Union

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

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