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Implementing GeoARK: The Geospatial Analytical Research Knowledgebase

This research focuses on the development and implementation of an interface to the Geospatial Analytical Research Knowledgebase (GeoARK), a spatially enabled big data informatics approach assembled around applications in health research and analytics. Example applications in telehealth reach, COVID-19 risk in rural situations, pathways for zoonotic disease spread, and contextual leukemia research will be provided.

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Neural information extraction in biomedical domain: issues and challenges

Much medical data today remain inaccessible thus limiting their impact on patient care. Images and illustrations, scientific articles, and free-text reports do not allow for easy extraction and re-use of the knowledge they contain. They lack the structure and metadata necessary for automated processing and annotation. The resources required to collect and annotate manually are

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Applied AI in CDSS in Medicine: A Systematic Review

Objective: Clinical decision support systems (CDSS) are continuously developing to solve medical problems and try to improve healthcare management, which has shown a significant result in reducing medical errors and improving multiple healthcare processes. These days, artificial intelligence (AI) becomes more influential in healthcare supporting physicians to make a clinical decision.  Materials and Methods: A systematic review

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Contrast Data Mining and Pattern Discovery for Glaucoma Risk Assessments

Glaucoma is the second leading cause of irreversible blindness across the world, about 70 million people have glaucoma, and 4.4 million people are blind due to undiagnosed glaucoma by optic nerve damage worldwide. Studies show that early prediction is the best way to prevent irreversible blindness. To address this problem, we applied a subgroup contrast

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Evaluation of chronic disease education & health information quality using online social networks & communities

Chronic diseases such as diabetes, cancer and mental illness are the leading causes of morbidity and disability. The total cost in the United States was $327 billion for diagnosed diabetes, 80.2 billion for cancer and $193.2 billion for serious mental illness. Chronic diseases rely a great deal on patient education and self-management and social media

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Evaluation of Provider Documentation Patterns as a Tool to Deliver Ongoing Patient-Centered Diabetes Education and Support

Diabetes is one of the most common chronic diseases in the world. As a disease with long term complications requiring changes in management, it requires ongoing diabetes self-management education and support (DSME/S). In the United States, however, only a small proportion of people with diabetes receive DSME/S. The diabetes education that providers deliver during follow

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Drug Repositioning for Subgroup discovery and Precision Medicine Implementation

Drug discovery is a high-cost, time-consuming, and labor-intensive process. With the declined approval rate for new drugs by the FDA, developing drug repositioning frameworks becomes crucial for improving patient care. Drug repositioning, known as old drugs for new uses, is an effective strategy to find new indications for existing drugs and is highly efficient, low-cost,

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Hierarchical agglomerative clustering of eusocial bee proteins

The assembly and annotation of the European Honey bee (Apis mellifera) genome has predicted more than 15,000 protein-coding genes and became the foundation for studies of nature and evolution of eusociality. Since then, other eusocial bee genomes have been sequenced, providing an excellent opportunity to seek additional insight into unique traits of eusocial bees at

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Mutational Forks: Inferring Pathway Deregulation Based on Patient-Specific Genomics Profiles

The precise mechanism behind treatment resistance in cancer is still not fully understood. Despite advances in precision oncology, there is a lack of the tools that help to understand a mechanistic picture of treatment resistance in cancer patients. Existing enrichment methods heavily rely on quantitative data and limited to analysis of differentially expressed genes, ignoring

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Extension of the informatics framework for the structurization of free text diagnostic reports

In this seminar presentation, we will briefly discuss our recent project to extend our informatics pipeline for the structurization of free-text diagnostic reports with an information theory-based approach. We will focus on the steps of this approach that are for quantifying and measuring information in free text diagnostic reports. This is a work in progress.

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