Zhijian Luan
Date:03-17-2022
Time:3:30PM-4:00PM
Location:2501 Student Center
Atrial fibrillation (AFib) is the most common irregularity of heartbeats. it can cause significant symptoms and impair heart function and daily life. 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
Read MoreLi Su
Date:03-10-2022
Time:4:00OPM-4:30PM
Location:2501 Student Center
Human Q fever is a worldwide zoonotic disease caused by intracellular Gram-negative bacterium, Coxiella burnetii. Human Q fever has high infectious nature. However, there is no FDA approved vaccine in the US. Previous studies showed that after serial passages in eggs and tissue cultures, C. burnetiid undergoes a lipopolysaccharide (LPS) phase variation in which its
Read MoreOlha Kholod
Date:03-10-2022
Time:3:30PM-4:00PM
Location:2501 Student Center
Phenotypic and genotypic heterogeneity are characteristic features of cancer patients. To tackle patients’ heterogeneity, immune checkpoint inhibitors (ICIs) represent one of the most promising therapeutic approaches to treat cancer. However, 50% of cancer patients that are eligible for treatment with ICIs will not respond well to this kind of therapies. Over the years, multiple patient
Read MoreHumayera Islam
Date:03-03-2022
Time:4:00pm-4:30pm
Location:2501 Student Center (Leadership Auditorium)
Successful implementation of data-driven artificial intelligence (AI) applications requires access to large datasets. Healthcare institutions can establish coordinated data-sharing networks to address the complexity of large clinical data accessibility for scientific advancements. However, persisting challenges from controlled access, safe data transferring, license restrictions from regulatory and legal concerns discourage data sharing among the in-network hospitals.
Read MoreJustin Hummel
Date:03-03-2022
Time:3:30pm-4:00pm
Location:2501 Student Center (Leadership Auditorium)
This study leverages clinicopathological data and genomic mutations based on a framework that includes a companion diagnostic template and a novel explainable AI algorithm to improve the selection of prospective patients for adjuvant therapy in colorectal cancer (CRC). Integrating these two emerging technologies may offer better solutions for assessing treatment outcomes by embracing a data-driven,
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