Current Advances in Valvular Heart Diseases
A special issue of Journal of Clinical Medicine (ISSN 2077-0383). This special issue belongs to the section "Cardiology".
Deadline for manuscript submissions: closed (15 March 2025) | Viewed by 2497
Special Issue Editor
Interests: valvular heart disease; valvular heart disease epidemiology; echocardiography
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Valvular heart diseases are a major public health problem associated with an increased risk of morbidity and mortality when not treated. Over the last decade, there has been a growing appreciation for the importance of the underlying mechanism of valvular heart disease and imaging, and the independent association of tricuspid valve regurgitation to reduced survival. Early and timely valvular heart disease intervention is associated with improved outcomes. However, due to their silent nature, valvular heart diseases frequently go underdiagnosed or are diagnosed late, often leading to no intervention or delayed intervention.
This Special Issue highlights strategies for the early diagnosis of valvular heart disease, such as machine learning or artificial intelligence, and the broadening understanding of mechanisms of valvular heart disease and their impact on the type and timing of intervention.
The topics of interest for this Special Issue include, but are not limited to, the following:
- Machine learning and artificial intelligence applications in valvular heart disease;
- Evaluation and management of primary and secondary mitral regurgitation;
- Evaluation and management of primary and secondary tricuspid valve regurgitation;
- Transcatheter valve therapies for aortic, mitral, and tricuspid valve disease;
- Minimally invasive surgical strategies for the treatment of valvular heart disease.
Dr. Vuyisile T. Nkomo
Guest Editor
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Keywords
- valve disease
- aortic valve stenosis
- aortic valve regurgitation
- mitral valve stenosis
- mitral valve regurgitation
- mitral annular calcification
- tricuspid valve regurgitation
- machine learning
- artificial intelligence
- echocardiography
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