Machine Learning and Deep Learning Applications in Healthcare
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biomedical Engineering and Biomaterials".
Deadline for manuscript submissions: 30 November 2024 | Viewed by 1137
Special Issue Editors
Interests: artificial intelligence; machine learning; deep learning; medical decision support systems; biomedical diagnostic techniques; personalized medical treatments; molecular sciences; medical imaging
Special Issues, Collections and Topics in MDPI journals
2. Medical Analysis Expert Group, Instituto de Investigación Sanitaria de Castilla-La Mancha (IDISCAM), 45071 Toledo, Spain
Interests: machine learning; biomedical signal processing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Deep learning is one of the research topics that attracts a lot of attention from healthcare system researchers. Compared to traditional machine learning methods, deep learning algorithms demonstrate their ability to train models from large datasets and images.
The computational capacity of deep learning models has enabled fast, accurate, and efficient operations in healthcare. Deep learning networks are transforming patient care and play a fundamental role in healthcare systems in clinical practice. Computer vision, natural language processing, and reinforcement learning are the most used deep learning techniques in healthcare. Moreover, these algorithms have significantly outperformed the performance of traditional methodologies for computer vision, natural language processing, robotics, and other fields.
This Special Issue on “Machine Learning and Deep Learning Applications in Healthcare” will focus on research works on the latest applications of deep learning in data analysis in different areas of healthcare research. The topics of interest for this Special Issue include, but are not limited to, the following:
- Healthcare data analytics;
- Medical imaging;
- Deep learning in time series processing;
- Biomedical diagnostic techniques;
- Personalized medical treatments;
- Predictive Modelling for Improving Healthcare;
- Medical decision support systems;
- Multimodal data processing and analysis for smart health;
- Medical systems based on big data and artificial intelligence;
- Artificial intelligence;
- Other related topics regarding healthcare, deep learning, and biomedical engineering.
Dr. Jorge Mateo Sotos
Dr. Ana María Torres Aranda
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.
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Keywords
- machine learning
- deep learning
- big-data enabled healthcare systems
- biomedical diagnostic techniques
- diagnostic imaging
- medical decision making
- digital pathology
- digital radiology
- artificial neural networks
- artificial intelligence
- smart health
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