학술논문

A text mining approach to automated healthcare for the masses
Document Type
Conference
Source
IEEE Global Humanitarian Technology Conference (GHTC 2014) Global Humanitarian Technology Conference (GHTC), 2014 IEEE. :28-35 Oct, 2014
Subject
Communication, Networking and Broadcast Technologies
Engineered Materials, Dielectrics and Plasmas
Engineering Profession
General Topics for Engineers
Geoscience
Photonics and Electrooptics
Power, Energy and Industry Applications
Robotics and Control Systems
Signal Processing and Analysis
Transportation
Discharges (electric)
Text mining
Medical diagnosis
Monitoring
Vectors
Diseases
Medical Diagnosis
Information Retrieval
Machine Learning
Text Mining
Language
Abstract
There is a tremendous amount of attention being focused on improving human health these days. The World Health Organization (WHO) statistics show that disease and mortality rate greatly depend on access to proper healthcare, which is not available to a vast majority of the global population. This technical paper presents our vision of automating some of the healthcare functions such as monitoring and diagnosis for mass deployment. We explain our ideas on how machines can help in this essential life supporting activity. Diagnosis part of the problem has been researched for long, so we set out working on this first, while the remaining is still in idea stage. We give insights into our work on automating medical diagnosis using text mining techniques and include some initial results.