@inproceedings{b5f05212931b4fffbc36dd34da8c2158,
title = "A Systematic Literature Review: Role of AI Algorithms for Automated Diagnosis of Diabetic Cardiac Autonomic Neuropathy [DCAN]",
abstract = "Cardiac autonomic neuropathy (CAN) is one of the most serious complications of diabetes known as DCAN. It is a complexity of Diabetes Mellitus (DM) that is allied with extended hazards of cardiovascular mortality. The management along with early detection of DCAN is significant as early intervention can forestall further disease progression. At present, the Ewing battery is the standard clinical method for assessing DCAN. However, it cannot distinguish sub-clinical CAN and it also requires patient cooperation. In this paper, a systematic literature review has been represented which focuses on information-digging strategies in consideration of AI technologies. In this paper, various strategies, methods, and algorithms are compared and represented with their results which are used for Classification, Automated Diagnosis, Detection, and Early prediction of DCAN tasks.",
keywords = "AI technologies, Automated detection, Cardiac autonomic neuropathy, data mining, Deep Learning, Diabetes, diabetes complications, machine learning",
author = "Mayura Nagar and Pooja Raundale and Ahsan Khandoker and Herbert Jelinek",
note = "Publisher Copyright: {\textcopyright} 2022 Bharati Vidyapeeth, New Delhi.; 9th International Conference on Computing for Sustainable Global Development, INDIACom 2022 ; Conference date: 23-03-2022 Through 25-03-2022",
year = "2022",
doi = "10.23919/INDIACom54597.2022.9763159",
language = "British English",
series = "Proceedings of the 2022 9th International Conference on Computing for Sustainable Global Development, INDIACom 2022",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "669--673",
booktitle = "Proceedings of the 2022 9th International Conference on Computing for Sustainable Global Development, INDIACom 2022",
address = "United States",
}
