Medicine and Health Sciences Commons^™

Pulmon-C: A Real-Time Monitoring Framework Of Pulmonary Function, Md Saiful Islam, Maria Valero, Shahriar Hossain

Symposium of Student Scholars

This project will develop PulMon-C, a real-time monitoring framework of pulmonary function to diagnose COVID-19 patients who are being self-quarantined at home. The tool will identify anomalies in breathe rate and predict pulmonary deterioration to raise alert for immediate actions. The uniqueness of the tool is using non-invasive sensors placed under-mattress that are able to communicate data about the respiratory signal. The customer segment of PulMon-C will be the diagnosed COVID-19 patients and healthcare providers. PulMon-C will assist with the remote monitoring of COVID-19 patients as an urgent need in the USA and will bring larger impact in delivering …

Impact Of Covid-19 On Health Disparities In The United States - A Preliminary Study, Alina Panjwani

Symposium of Student Scholars

Health disparities are the differences in health outcomes and health status among people belonging to different groups. This means that people with low socioeconomic status, old age, racial and ethnic minorities, who are often those with limited access to healthcare may often face a higher disease burden and experience worse health outcomes. The current pandemic of Coronavirus 2019 (COVID-19), caused by the novel coronavirus SARS-CoV-2, provides a painful reminder of why inequities harm all of us as the devastating impact of the pandemic is apparent. This paper examines the differences in and possible cause of the rates of COVID infections, …

A Study Of Covid Tweet: Text Mining And Sentiment Analysis., Tiffany Agiri

Symposium of Student Scholars

A Study of COVID Tweet: Text Mining and Sentiment Analysis.

Tiffany Agiri, BSIT

Advisor: Dr. Chi Zhang, Associate Professor of Information Technology

Abstract

How do the tweets of two polarizing news outlets differ regarding COVID-19, and what can we draw from this data? CNN and Fox News are the two opposing news sources whose tweets we used to conduct our research, with the objective to analyze the tweet most frequently discussed terms on Covid-19 using Natural Language Processing and learn what kind of sentiments the terms are conveying, in each news source’s tweets. Through the use of the Python library …

R-Lstm: Time Series Forecasting For Covid-19 Confirmed Cases With Lstm-Based Framework, Mohammad Masum

Symposium of Student Scholars

The coronavirus disease 2019 (COVID-19) caused a pandemic outbreak affecting 213 nations worldwide. Global policymakers are imposing many measures to slow and reduce the rapid growth of infections. On the other hand, the healthcare system is encountering significant challenges for a massive number of COVID-19 confirmed or suspected individuals seeking treatment. Therefore, estimating the number of confirmed cases is necessary to provide valuable insights into the growth of the outbreak and facilitate the policy-making process. In this study, we apply ARIMA models as well as LSTM-based recurrent neural networks to forecast the daily cumulative confirmed cases. The LSTM architecture generates …

An Investigation On Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset And Its Effectiveness, Md Jobair Hossain Faruk

Symposium of Student Scholars

Neurotechnology describes as one of the focal points of today’s research around the domain of Brain-Computer Interfaces (BCI). The primary attempts of BCI research are to decoding human speech from brain signals and controlling neuro-psychological patterns that would benefit people suffering from neurological disorders. In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain onto a digital screen introduced by Facebook Reality Laband University of California San Francisco. Then, we study a recently …