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VOLUME 4 , ISSUE 4 ( October-December, 2018 ) > List of Articles

ORIGINAL ARTICLE

A Deep Learning-based Approach in Automated Detection of Genu Valgum

Satyake Bakshi, Sathya A

Keywords : Convolutional neural networks, Genu valgum, Knock knees,Artificial neural network

Citation Information : Bakshi S, A S. A Deep Learning-based Approach in Automated Detection of Genu Valgum. J Med Sci 2018; 4 (4):91-94.

DOI: 10.5005/jp-journals-10045-0095

License: CC BY-NC 4.0

Published Online: 00-12-2018

Copyright Statement:  Copyright © 2018; Jaypee Brothers Medical Publishers (P) Ltd.


Abstract

This paper investigates an attempt to detect genu valgums in patients. A typical diagnosis of genu valgum is based on the observation of how the alignment of the knees are during standing or if legs have different lengths. This system is an attempt to computationally draw a line between what kind of knee is a “genu valgum” and a “normal” knee. This system would also focus on an approach to increase the accuracy of the model to correctly classify this shape “disorder”. Authors would rely on the creation of our dataset from Physiobank (modified) test it on a live subject to establish the standard of performance.


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  1. McDade W. Bow legs and knock knees. Pediatric Clinics of North America. 1977 Nov 1;24(4):825-839.
  2. ‘Knock knees’ a challenge for athletes, coaches. 2012 June 10. Retrieved from http://www.columbian.com/news/2012/ jun/11/knock-knees-a-challenge-for-athletes-coaches/.
  3. Lawrence R. Using neural networks to forecast stock market prices. University of Manitoba. 1997 Dec 12;333.
  4. Egmont-Petersen M, de Ridder D, Handels H. Image processing with neural networks—a review. Pattern recognition. 2002 Oct 1;35(10):2279-2301.
  5. Tomè D, Monti F, Baroffio L, Bondi L, Tagliasacchi M, Tubaro S. Deep convolutional neural networks for pedestrian detection. Signal processing: image communication. 2016 Sep 1;47:482-489.
  6. Esteva A, Kuprel B, Novoa RA, Ko J, Swetter SM, Blau HM, et al. Dermatologist-level classification of skin cancer with deep neural networks. Nature. 2017 Feb;542(7639): 115.
  7. Sharma K, Kaur A, Gujral S. Brain tumor detection based on machine learning algorithms. International Journal of Computer Applications. 2014 Jan 1;103(1):7-11.
  8. Tetko IV, Livingstone DJ, Luik AI. Neural network studies. 1. Comparison of overfitting and overtraining. Journal of Chemical Information and Computer sciences. 1995 Sep 1;35(5):826-833.
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