PATIENT CLASSIFICATION USING DEEP LEARNING
Authors
Shrestha, Sangam
Issue Date
2019
Type
Thesis
Language
Keywords
Alzheimer's , Classification , Deep Learning , Early Diagnosis , Influenza , machine learning
Alternative Title
Abstract
With diseases like Alzheimer's and Influenza still claiming lives, there have been a lot of methods developed in order to combat these diseases. There is a possibility that the key to finding susceptibility towards a disease might lie in the patient's genetic makeup. The purpose of this thesis is to see if it is possible to predict whether a person is likely to suffer from a certain disease based on gene expression values. In order to achieve this goal, a computational based approach was adopted. Currently, artificial intelligence is producing results that were deemed not possible a few years ago. Moreover, deep learning, one specific branch of artificial intelligence, has been used to produce useful results. It has been used in many new technologies such as self-driving cars, natural language processing, and many other automated systems. This research came up with a method that makes use of a deep learning approach and found that it is indeed effective in classifying patients.