Differential Diagnosis of Tuberculosis and Pneumonia using Machine Learning
Author(s) -
Anusha Illur,
Aekhata Nanda,
Mansoor Ahmed,
Aiyesha Sadiya,
Eshwar Rao
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.f1049.0486s419
Subject(s) - machine learning , artificial intelligence , computer science , domain (mathematical analysis) , pneumonia , health care , tuberculosis , differential diagnosis , medicine , mathematics , pathology , mathematical analysis , economics , economic growth
Machine learning has become one of the top most emerging technologies in this era of digital revolution. The machine learning algorithms are being used in various fields and applications such as image recognition, speech recognition, classification, prediction, medical diagnosis etc. In medical domain, machine learning techniques have been successfully implemented to improve the accuracy of medical diagnosis and also to improve the efficiency and quality of health care. In this paper, we have analyzed the existing health care practice system and have proposed how machine learning techniques can be used for differential diagnosis of Tuberculosis and Pneumonia which are often misdiagnosed due to similar symptoms at early stages.
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