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Relational object extraction from a medical text corpus, and application of machine learning techniques to classify symptoms and conditions.

Ruby 0.02% Objective-C 87.27% C 2.81% Shell 0.68% Python 9.22%

thesis's Introduction

# Introduction

This repository contains the work undertaken by myself (Harrison Sweeney) as part of my final year thesis in Mechatronic Engineering at UWA, Australia. It involves analysing a text corpus of medical data containing symptoms, causes, treatments, and drugs to identify relations between extracted data points. This information is then stored in a graph database (Neo4j), where is is able to be queried and manipulated. Down the line, an iOS app will be developed to interact with the graph database.

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