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Tool development for resolving and visualizing irregular heartbeats measured by cardiac magnetic resonance
Presenter:

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

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Single-cell immune profiling of Q fever vaccination in mice
Presenter:

Li 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

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Identification of biomarkers and therapeutic combinations for immune checkpoint inhibitors (ICIs) using explanatory subgroup discovery for cancer patients without EGFR mutation
Presenter:

Olha 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

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A Privacy-Preserved Transfer Learning Concept to Predict Diabetic Kidney Disease at Out-of-Network Siloed Sites Using an In-Network Federated Model on Real-World Data
Presenter:

Humayera 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.

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Survival analysis in Stage II and III Colorectal Cancer Patients Using Novel Exploratory Data Mining
Presenter:

Justin 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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