With current methods, the diagnosis of diseases by professionals is based on the expressed symptoms observable to the professional. Because of this dependence on humans and the training or focus of the professional, diagnosis and description of the severity of a disease is largely subjective. This is where computers come in. In an attempt to change this subjective assessment to an objective one – so that diagnosis is more reliable and understandable – devices and algorithms which look at samples of speech to make a diagnosis are being developed. This project looks at the different strategies of using computers to analyze speech. The analysis of speech can gather many things about the speaker, from age to race; this project focuses on the severity or even the existence of a disease. With traits of speech like speaking rate, pitch, and articulation, the severities of a disease like Parkinson’s can be objectively determined. Another method is through the cough. Similar techniques can be used to look at the characteristics of a cough and what the implications of that cough may be. My goal in this project is to understand the complexity of such algorithms and possibly contribute to the making of one. There are many unexplored speech characteristics, which could improve a computer’s decision making, and I attempt to help develop algorithms for those characteristics, specifically focusing on the cough.