A Systematic Literature Review: Role of AI Algorithms for Automated Diagnosis of Diabetic Cardiac Autonomic Neuropathy [DCAN]
Author:
Affiliation:
1. Sardar Patel Institute of Technology,MCA Department,Mumbai,India
2. Healthcare Engineering Innovation Center (HEIC), Khalifa University,Department of Biomedical Engineering,Abu Dhabi,United Arab Emirates (UAE)
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9763090/9763103/09763159.pdf?arnumber=9763159
Reference36 articles.
1. Diabetic Neuropathy: A Position Statement by the American Diabetes Association
2. Feasibility of combining heart rate variability and electrochemical skin conductance as screening and severity evaluation of cardiovascular autonomic neuropathy in type 2 diabetes
3. A Deep Learning Approach to Predict Diabetes’ Cardiovascular Complications From Administrative Claims
4. Screening Cardiovascular Autonomic Neuropathy in Diabetic Patients With Microvascular Complications Using Machine Learning: A 24-Hour Heart Rate Variability Study
5. Early detection of cardiovascular autonomic neuropathy: A multi-class classification model based on feature selection and deep learning feature fusion
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1. A state-of-the-art review on computational methods for predicting the occurrence of cardiac autonomic neuropathy;Internet of Things and Machine Learning for Type I and Type II Diabetes;2024
2. State-of-the-art in exploring Integration of Machine Learning and Deep Learning Techniques with Medical Parameters for Diabetic Clinical Decision Support;2023 6th International Conference on Advances in Science and Technology (ICAST);2023-12-08
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