Volgenau School of Engineering Graduate Research
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Browsing Volgenau School of Engineering Graduate Research by Subject "Artificial intelligence"
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Item Comparative Analysis of Medication Based on Machine Learning Models(2021-04-28) Kouser, Nashid; Barekzai, SaraOur society is seeing a sharp rise in the number of people suffering from complicated chronic diseases. Presently, 6 in 10 adults in the United States have a chronic disease. This is the leading cause of death and the leading driver of the Nation's $3.8 Trillion in Annual Health Care Costs. With that figure predicted to grow, clearly, something is lacking from the one-size. the fits-all paradigm of traditional medicine. Caring for this new population requires an entirely different mindset; this is where functional medicine steps in. Functional medication can help prevent disease thus potentially proving to be more cost-effective for the insured and insurer overall in the long term. However, there are approximately 1400 functional medicine practitioners across the U.S., and a little under 350 that accept insurance. We analyze health data from a new point in this research.Item Data Analytic approach for Opinion Mining in Important Events(2021-04-28) Xu, GeThe best way to predict the future is to study the past. This is one of the basic ideas behind big data analytics. As an example, some presidents utilize a data-driven approach in their campaign for the elected presidency. The campaign had a data analytics team of people. It shows how deeply data analytics has impacted the world, from recommending products to customers on e-commerce sites (i.e., using predictive analytics) to electing the most powerful officials in the free world. Big data analytics is truly everywhere (Big Data Analytics and Predicting Election Results, 2019).In this work, we analyze important events based on online data.Item Machine Learning Models and Transfer Models for Measuring Impact of the Pandemic on Communities(2021-04-28) Berdibekov, TimurThis paper studies the relationship between the 2019 Novel Coronavirus (COVID-19) pandemic, its public health and economic impact, and rates of economic inclusion and access to banking services throughout the pandemic in the United States. For select U.S. counties, this paper examined COVID-19 infection and mortality rates, unemployment rates and the number of bank closures, and the rate of economic inclusion to discover any notable relationships. Lastly, select features are evaluated for the predictive capability of the county and county-equivalent rates of unbanked households to better inform policy making given that the unbanked household rates are unknown for most counties.Item Social Media Analytics for Opinion Mining of Important Events(2021-04-28) Hapikul, SuchadaStatistics of various aspects of each political campaign have been counted on multiple websites. Big data analytics can analyze each candidate's "tags," the slogans and strategies of different candidates, and the public's attention to these keywords and analyze the public trends. Social media can use big data statistics and judgment to make people's decisions deviate and guide the whole public opinion and even change many people's original intention. This work uses data analysis methods in Social media to understand the people's opinion.Item Tools for Identifying AI Biases for Machine Learning Models(2021-04-28) Adchariyavivit, Patcharaporn; Crow, Austin; Golden, VictoriaThere is no doubt about the usefulness of machine learning in today’s data environment. Machine learning algorithms are used across many domains and across a variety of problems. These algorithms are seen in e-commerce such as Amazon’s recommendations , financing through loan applications, image processing, autonomous vehicles, and speech recognition among many others. Acknowledging the market penetration of machine learning and its relevance to many big data related challenges, it is important to address the effect of bias in machine learning.