Business Commons^™

A Systematic Literature Review Of Ransomware Attacks In Healthcare, Jasler Klien Adlaon

Electronic Theses, Projects, and Dissertations

This culminating experience project conducted a Systematic Literature Review of ransomware in the healthcare industry. Due to COVID-19, there has been an increase in ransomware attacks that took healthcare by surprise. Although ransomware is a common attack, the current healthcare infrastructure and security mechanisms could not suppress these attacks. This project identifies peer-viewed literature to answer these research questions: “What current ransomware attacks are used in healthcare systems? “What ransomware attacks are likely to appear in the future?” and “What solutions or methods have been used to prepare, prevent, and recover from these attacks?” The purpose of this research is …

A Study Of Heart Disease Diagnosis Using Machine Learning And Data Mining, Intisar Ahmed

Electronic Theses, Projects, and Dissertations

Heart disease is the leading cause of death for people around the world today. Diagnosis for various forms of heart disease can be detected with numerous medical tests, however, predicting heart disease without such tests is very difficult. Machine learning can help process medical big data and provide hidden knowledge which otherwise would not be possible with the naked eye. The aim of this project is to explore how machine learning algorithms can be used in predicting heart disease by building an optimized model. The research questions are; 1) What Machine learning algorithms are used in the diagnosis of heart …

Analysis On Suicidal Ideation Among Adolescents (12-17 Years) In The Usa, Himani Raturi

Electronic Theses, Projects, and Dissertations

Suicide is one of the leading health concerns in United States among adolescents and the presence of suicidal ideation (SI) is quite high, with ~20-30% of adolescents reporting it at some point. Though we have seen growth and development in the prevention of suicide, there is limited research on the ability to identify the adolescents which might be at risk for SI. The objective behind the project is to identify adolescents with SI using machine learning.

The project shows statistics from different articles on adolescents in the U.S. For this study, adolescent data was taken from NSDUH 2018. Moreover, detailed …