Proceedings of the International Conference on Industrial Engineering and Operations Management
Dubai, UAE, March 10-12, 2020
© IEOM Society International
Artificial Intelligence Technique For Detecting Bone
Irregularity Using Fastai
Meghna Hooda and Shravankumar Bachu
Department of Computer Science
SRM University
Delhi NCR, Haryana
hoodameghna@gmail.com, shravan2311@hotmail.com
Surjeet Dalal
Department of Computer Science
SRM University
Delhi NCR, Haryana
surjeet.d@srmuniversity.ac.in
Piya Ghosh
Department of Industrial and Management Engineering
Indian Institute of Technology
Kanpur, Uttar Pradesh
piyagh@iitk.ac.in
Abstract
A bone abnormality is a medical condition which is caused by physical damage or diseases. There are many factors
which can lead to various abnormalities. An irregularity in a bone is generally diagnosed by orthopedician and
radiologists using x-ray images of the affected bone. Bone abnormalities affect more than a billion people in the
world. With more than 30 million emergency visits annually, there is a lack of expertise. Although computer aided
diagnosis is still very limited in the world. They are mostly confined to research projects and there’s been no real
world applications. For the past few years there has been a great leap in the development of Artificial Intelligence
which now makes it possible to implement and test deep learning models in the medical field. One can get an
appropriate amount of data for these implementations. MURA is a database that was made available by Stanford
University for testing purposes in a target of achieving a best model for detecting bone abnormalities. Our
paper mainly focuses on the advancement in medical imaging technologies targeting the diagnosis at the level of
experts for improving health care access. We used python, as a programming tool, and fastai, to process images and
implement the model for abnormality detection. The proposed model follows a feed forward network resulting in a
good accuracy rate.
Keywords
x-ray, artificial intelligence, neural network, python, fastai
1. Introduction
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