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Special Issue "Non-invasive Diagnostics for Cardiovascular Diseases"
Deadline for manuscript submissions: closed (31 July 2018).
Interests: biomedical signal processing; digital medicine; data analysis; health care; machine learning; computer science; psychology and neuroscience; biomedical and health informatics; women's healthcare and wellness
The development of non-invasive cardiovascular disease diagnostics necessitates ongoing knowledge and skills updates to match the current demands and progress in the field. In today’s chaotic world, there is an increasing trend to seek out simple, non-invasive solutions for complex problems that can increase efficiency, reduce resource consumption, and improve scalability. This desire has spilled over into the world of science and research, where many disciplines have taken to investigating and applying more simplistic non-invasive approaches to replace existing invasive technologies that are often costly and require high levels of training. Interestingly, through a review of current literature it seems that invasive diagnostic methods continue to be the gold standard with limited effort towards exploring noninvasive alternatives. Theoretically, a shift towards more simple and non-invasive solutions could yield equal or better results than invasive methods, in addition to needing less resources and training.
The purpose of this Special Issue is to bring together researchers and practitioners from multiple areas of expertise including biology, medicine, engineering and other physical sciences that are interested in studying and using non-invasive techniques for diagnosing diseases. A diversity of non-invasively measured signal types is included in this research area including electrical, image, audio and other biological sources of information. Developing efficient diagnostic tools requires multidisciplinary research that integrates knowledge from medicine (e.g., disease etiology, disease annotation, diagnostic accuracy), engineering (e.g., signal processing, modelling), computer science (e.g., pattern recognition, machine learning, computational intelligence techniques) and other related areas.
Dr. Mohamed Elgendi
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. Diseases is an international peer-reviewed open access quarterly 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 1000 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.
- Electrocardiography and Holter Monitoring
- Photoplethysmogram (Pulse Ox)
- Heart sounds (cardiac auscultation)
- Echocardiogram (echo)
- Chest X-Ray
- Cardiac Computed Tomography
- Exercise Stress Test
- Myocardial perfusion scintigraphy
- Positron Emission Tomography-PET
- Coronary angiography CT (Multislice CT Angiography)
- Cardiac MR