Deep Neural Networks for Smart Healthcare Systems

Dear Colleagues,

Chronic and complex illnesses have an important economic impact on national healthcare systems. The advancement of wearable technology and medical sensors has led to the collection of a significant amount of medical and healthcare data for individual patients; however, artificial intelligence and, more specifically, deep learning approaches allow the building of smart healthcare systems. In view of reducing the elevated costs associated with disease treatment and hospitalization, early and improved diagnosis can be achieved by taking into consideration medical data recorded with various types of medical sensors (biomedical images, biomedical signals and parameters). The interpretation of this heterogeneous data and intelligent human–computer interaction systems will generate better prevention and diminished costs in cases of chronical and complex illnesses.

The present Special Issue will address the application of deep neural networks in the field of (semi)automatic disease diagnosis. It welcomes original contributions that focus on novel deep learning approaches and digital signal/imaging processing that can be used to extract and classify relevant diagnostic information from multimodal and/or multichannel medical and healthcare data. Reviews focused on the latest achievements of scientific research and emerging techniques are also welcome.

Possible topics include but are not limited to deep neural network approaches for automatic diagnosis and the classification of neurodegenerative diseases, arrythmias, COVID-19, pulmonary diseases, fetal wellbeing and septicemia, as well as smart healthcare systems.

Dr. Dragos D. Taralunga
Dr. Bogdan C. Florea
Dr. Anamaria Radoi
Prof. Dr. G. Mihaela Neagu
Guest Editors

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