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Development of AI Models for Remote Sensing City Fitness

Tracking a city’s 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

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Tool development for resolving and visualizing irregular 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 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

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

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

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

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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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

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Developing a Web-Based Interface to Manage Sensor Technologies in the Homes of Older Adults 

Internet of Things sensors capture daily activities and physiological data that can improve care for older adults.  Sensors have the potential to enable health coaching for self-management and care coordination by connecting individuals to care providers and informal caregivers. However, remote management of diverse sensor technologies and integration of disparate data for decision-making are major barriers

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The impact of treatment adjustment in breast cancer by Cerner Real-World Data during pandemic

The global burden of the ongoing COVID-19 pandemic has predominantly been measured using metrics like case numbers, hospitalizations and deaths. However, the short-term health impacts are more difficult to capture, especially for breast cancer(BC) patients. An expert opinion formulated by multiple national organizations provided preliminary guidance on the prioritization and treatment of breast cancer(BC) during

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The Soybean Allele Catalog Tool: A Web-Based Interactive Tool for Gene Alleles Discovery

The advancement of sequencing technologies has made a plethora of whole genome sequenced (WGS) data publicly available. However, utilizing the raw WGS data will not generate promising research outcomes for agriculture. To solve this problem, the Soybean Allele Catalog Tool (https://soykb.org/SoybeanAlleleCatalogTool/search.php) has been developed to assist researchers in gaining insights into soybean genotypes associated with

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