Journal of Diabetic Complications & Medicine

Andrei V Kelarev

Publications

• Research Article
  Machine Learning Methods for Automated Detection of Severe Diabetic Neuropathy
  Author(s): Herbert F Jelinek, David J Cornforth and Andrei V KelarevHerbert F Jelinek, David J Cornforth and Andrei V Kelarev
  
  Objective: The present study aimed at investigating machine learning methods for automated detection of severe diabetic neuropathy. Severe diabetic neuropathy represents a significant neurological problem in diabetes as it requires urgent intervention to reduce the risk of sudden cardiac death. Automated detection provides a tool that can be applied to clinical data and for identifying comorbidities that can trigger diagnosis and treatment. Methods: We applied multi scale Allen factor to determine heart rate variability, a marker for diabetic neuropathy from ECG recordings as features to be used for the machine learning methods and automated detection. The major innovation of this work is the introduction of a new Graph-Based Machine Learning System (GBMLS). This method is intended to enhance the effectiveness of the .. Read More»
  DOI: 10.4172/2475-3211.1000108

  Abstract PDF