The following publications are possibly variants of this publication: 
- Heart rate independent QT variability component can detect subclinical cardiac autonomic neuropathy in diabetesMohammad Hasan Imam, Chandan K. Karmakar, Ahsan H. Khandoker, Herbert F. Jelinek, Marimuthu Palaniswami. embc 2016: 928-931 [doi] 
 - Screening Cardiovascular Autonomic Neuropathy in Diabetic Patients With Microvascular Complications Using Machine Learning: A 24-Hour Heart Rate Variability StudyMohanad Alkhodari, Mamunur Rashid, Mohammad Abdul Mukit, Khawza I. Ahmed, Raqibul Mostafa, Sharmin Parveen, Ahsan H. Khandoker. access, 9:119171-119187, 2021.  [doi] 
 - Detection of Cardiac Autonomic Neuropathy using Linear Parametric Modeling of QT dynamicsMohammad Hasan Imam, Chandan K. Karmakar, Ahsan Khandoker, Herbert F. Jelinek, Marimuthu Palaniswami. cinc 2013: 1019-1022 [doi] 
 - Automated Selection of Measures of Heart Rate Variability for Detection of Early Cardiac Autonomic NeuropathyDavid Cornforth, Mika P. Tarvainen, Herbert F. Jelinek. cinc 2014: 93-96 [doi] 
 - Principal component analysis of heart rate variability data in assessing cardiac autonomic neuropathyMika P. Tarvainen, David J. Cornforth, Herbert F. Jelinek. embc 2014: 6667-6670 [doi] 
 - A Comparison of Nonlinear Measures for the Detection of Cardiac Autonomic Neuropathy from Heart Rate VariabilityDavid Cornforth, Herbert F. Jelinek, Mika Tarvainen. entropy, 17(3):1425-1440, 2015.  [doi] 
 - Reliability of heart-rate-variability features derived from ultra-short ECG recordings and their validity in the assessment of cardiac autonomic neuropathyD. Wehler, Herbert F. Jelinek, A. Gronau, N. Wessel, Jan F. Kraemer, Robert Krones, T. Penzel. bspc, 68:102651, 2021.  [doi]