Cutting-Edge Applications of Machine and Deep Learning in Biomedical Signal and Image Processing
A special issue of Bioengineering (ISSN 2306-5354). This special issue belongs to the section "Biosignal Processing".
Deadline for manuscript submissions: 15 December 2024 | Viewed by 911
Special Issue Editors
Interests: artificial intelligence; machine & deep learning; signal & image processing
Special Issues, Collections and Topics in MDPI journals
Interests: digital and statistical signal processing; speech processing; biomedical signal processing; applied machine learning
Special Issue Information
Dear Colleagues,
The development of advanced sensors optimized for translating biological and biomedical information into digital data is continually progressing, enhancing our ability to gather precise human physiology data to support diagnoses of various diseases. These devices collect information from numerous sources, including physiological signals and medical images. Critical data can be extracted to feed artificial intelligence models, including machine learning (ML) and deep learning (DP) algorithms, using advanced signal and image processing techniques to support decision-making across multiple domains.
This Special Issue is dedicated to presenting the latest discoveries, emerging concepts, and technological applications of ML and DP within the health context. We invite contributions on a wide range of topics, including but not limited to:
- Signal Processing ML-Based Analysis: This includes the analysis of signals such as EEG (electroencephalogram), EMG (electromyogram), ECG (electrocardiogram), FNIRs (functional near-infrared spectroscopy), and evoked potentials.
- Imaging ML-Based Analysis: Contributions can also cover the application of ML in analyzing medical imaging modalities like X-ray, PET (positron emission tomography), CT (computed tomography), MRI (magnetic resonance imaging), and SPECT (single-photon emission computed tomography).
- Wearable Bio-Technology Applications Supported by ML: Emerging wearable technologies that leverage ML algorithms to monitor and analyze physiological data in real time are also of great interest.
Prof. Dr. Pedro Miguel Rodrigues
Prof. Dr. Bruno Bispo
Prof. Dr. Joaquim Celestino
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- biosignal analysis
- medical image analysis
- machine learning
- deep learning
- wearable bio-technology
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