Recent Progress of Deep Learning in Healthcare
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: closed (15 July 2024) | Viewed by 1064
Special Issue Editor
Special Issue Information
Dear Colleagues,
The field of healthcare stands at the cusp of a transformation, driven by the rapid advancements in artificial intelligence. Deep learning, a subset of machine learning, has shown unprecedented success in interpreting complex data, making it a potent tool for clinical decision support, medical diagnostics, treatment planning, and disease prediction. By analyzing complex medical data, these algorithms enhance the management of chronic disease, improve diagnostic accuracy, and aid in early disease detection. They also revolutionize personalized medicine, tailoring treatments to individual genetic and health profiles. In drug development, deep learning accelerates the discovery and testing of new drugs. Additionally, it supports clinicians with decision-making tools and powers health monitoring wearables, offering real-time insights into patient health. This technology is not just transforming how healthcare is delivered, but also improving patient outcomes, making healthcare more accessible, effective, and personalized.
This Special Issue aims to provide a comprehensive overview of the current state and future potential of deep learning in healthcare. It features pioneering research demonstrating the use of these algorithms in applications to complex diseases, such as diabetes, dementia, and cardiovascular diseases, offering insights into the innovations that are set to redefine healthcare in the coming years.
Dr. Taiyu Zhu
Guest Editor
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Keywords
- deep learning
- personalized medicine
- digital health
- bioinformatics
- genomic data analysis
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