Special Issue "Selected Papers from Signal 2018: Machine Learning for Biomedical Data Processing"
A special issue of Machine Learning and Knowledge Extraction (ISSN 2504-4990).
Deadline for manuscript submissions: 30 June 2018
This Special Issue will collect a limited number of selected invited and contributed papers presented at MLFORBSP during the conference Signal 2018 which will be held at Nice, France, in May 2018. The conference website can be found at: http://www.iaria.org/conferences2018/SIGNAL18.html
Biomedical signal processing involves the treatment and analysis of bio-signal measurements. It is done in order to provide useful information which clinicians can use to make decisions. Novel signal processing methods have assisted in revealing information that entirely altered the previous approaches taken in the diagnosis of different diseases. In order to analyze biomedical signals, biomedical engineers use different types of signal processing and machine learning techniques. By using intelligent biomedical analysis tools, the signals can be analyzed by software to help physicians gain greater insights and to make better decisions in clinical assessments.
Nowadays, there is a great deal of interest in machine learning applications in health, biomedicine, and biomedical engineering. The recent advances in biomedical signal processing and machine learning have brought forth incredible progress to different areas in signal analysis and processing, including biometrics, medical data processing, etc. The application-oriented and data-driven bio-signal analysis and processing applications, not only benefit from the machine learning algorithms, but also encourage the development of intelligent techniques.
The purpose of this Special Issue is to present recent advances in signal processing and machine learning for biomedical signal analysis. We are targeting original research works in this field, covering new theories, algorithms, implementations, and applications for signal and data analytics. Potential topics of interests are related to recent advances in machine learning in signal analysis and processing, but are not limited to them:
- Biomedical Signal Processing and Analysis
- Biomedical Image Processing and Analysis
- Brain Computer Interface
- Human Machine Interfaces
- Neural Rehabilitation Engineering
- Biomedical Data processing for Big Data
- Information forensics and security
- The Internet of Things and RFID
- Machine learning for signal/image processing
- Signal/Image Processing for Brain Machine Interface
- Time-frequency and Non-stationary Biosignal Analysis
- Machine learning for biomedical signal/image processing
- Machine Learning in Biomedical Applications
- Biometrics with biomedical signals
Prof. Dr. Abdulhamit Subasi
Prof. Dr. Saeed M. Qaisar
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 papers will be 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. Machine Learning and Knowledge Extraction is an international peer-reviewed open access biannual journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) is waived for well-prepared manuscripts submitted to this issue. 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.