March 11, 2021

Dissertation Defense – Utilizing Blockchain Technology for Clinical Trial Optimization

Clinical trials are the cornerstone of treatment discovery because they provide comprehensive scientific evidence on the safety, efficacy, and optimal use of therapeutics. However, current clinical trials are facing multiple challenges such as patient recruitment, data capture, and overall management. There are various causes of patient recruitment challenges such as inefficient advertising models, complex protocols, and distant trial sites. Data inconsistency is the main challenge of the data capture process. Source data verification, a standard method used for data monitoring, is resource-intensive that can cost up to 25% of the total budget. The current clinical trial management system market is…

Feb. 11, 2021

Thyroid Cancer Informatics

Survival prediction is important both to clinicians and patients; ensuring the best course of treatment is selected to manage the thyroid cancer. In 2018, there was an estimated half a million new thyroid cancer diagnoses and 41,071 deaths. Unlike other tumors whose mortality has decreased over the last two decades, thyroid cancer mortality rates have increased. Existing risk stratification systems fail to account for microcarcinomas, which accounted for 28.6 percent of thyroid cancer diagnoses and 32.5 percent of papillary thyroid cancer diagnoses. They are also based upon a varying combination of 10 variables and have not considered newly identified variables available in current research. Additionally,…

Jan. 25, 2021

Building a Population-based Childhood Cancer Data Ecosystem: Challenges and Opportunities for Informatics and Data Science

Childhood cancer is a relatively rare disease diagnosed in over 16,000 U.S. children and adolescents (ages 0 – 19) each year.  While 84% of children with cancer survive 5 years or more, cancer remains the second leading cause of death in children after accidents. Molecular variations make all childhood cancers extraordinarily rare and difficult to study.  The Childhood Cancer Data Initiative (CCDI) of the National Cancer Institute recognizes the critical need to collect and analyze and share data to address this understudied cancer burden. Innovations in informatics methods and data science are clearly needed to assimilate new data sources, characterize the burden…

Nov. 10, 2020

Elucidate the Genome Evolution of Eusocial Corbiculate Bees Using Parent-progeny Sequencing Approach

Understanding the evolution of eusociality, defined by distinct reproductive and nonreproductive castes, at the molecular level, has always been an essential and highly challenging topic of biology. Eusociality has evolved multiple times independently and involved many incremental steps, resulted in intermediate levels of social complexity. The Apinae (corbiculate bees) consists of 4 tribes with a wide range of social complexity: orchid bees (Euglossini), bumble bees (Bombini), stingless bees (Meliponini), and honey bees (Apini); is an ideal group for comparative studies of eusocial evolution in Hymenoptera. The first sequenced genome of the honey bee Apis mellifera in 2006 has become a gateway for…

Oct. 20, 2020

Cancer Surveillance Informatics – Missouri Cancer Registry and Research Center

Cancer surveillance has to be able to monitor trends of cancer cases, subtypes of cancer, and cancer clusters to inform cancer control and policies related to cancer and cancer care. The increasing complexity and depth of cancer care, treatment, and other elements to describe a cancer case require cancer registries to capture data from a wide variety of sources by utilizing many informatics methods to integrate these data. Current and future developments include automated processing of electronic pathology reports, artificial intelligence, natural language processing NLP, and linkage of data sources to expand surveillance goals. Recent developments include a national virtual…

May 20, 2020

Artificial Intelligence Driven Framework for the Structurization of Free-Text Diagnostic Reports

Diagnosticians record, share, and store a wealth of data on patients, diseases, and biomedical processes in free-text diagnostic reports. To continue providing advanced biomedical services, healthcare organizations should efficiently and effectively perform complex data management, aggregate data resources, and ensure the interconnectivity and interoperability of biomedical data sets. However, free-text is a poor starting point for the computational analysis of complex biomedical information. For data management applications, diagnostic reports, biomedical test results, diagnostic images must be in a structured and machine-readable format. Free-text diagnostic reports lack data structure, making it challenging to extract information and use it for medical care…

April 15, 2020

New Algorithmic Strategies to Forecasting Contagions

Abstract Can tweets be really used to track and forecast an epidemic outbreak? Can we monitor a handful of individuals in a city or a social network to forecast virality? The problems we focus on occur in diverse areas: social networks, public health surveillance, and cybersecurity. This talk will comprise two parts. In the first part, we leverage graphical models to infer the progression of the flu from user tweets. We show how we can effectively and accurately track flu trends and peaks using millions of tweets harvested from Latin America. In the second part, we design social network sensors for early detection…

Feb. 12, 2020

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 was conducted to identify articles related to CDSS using AI algorithms. The original research was published between 2009 and 2019 in the English language. In a total of 3,687 identified articles, 1,112 articles were analyzed, and 199 articles are represented within this review.