Lakshimi P. Dasi, Georgia Institute of Technology, United States
Cardiovascular Ultrasound is calling for submissions to our Collection on Artificial intelligence in echocardiography.
For more information refer to the About the Collection section below.
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This Collection supports and amplifies research related to SDG3: Good Health and Well-Being.
Lakshimi P. Dasi, PhD, Georgia Institute of Technology, United States of America
Lakshmi Prasad Dasi, Ph.D., is an established researcher in the field of prosthetic heart valves, cardiovascular biomechanics, biomaterials, and devices. He is currently a tenure Professor of Biomedical Engineering, at Georgia Institute of Technology while holding the Rozelle Vanda Wesley Endowed Professorship. He has held positions at The Ohio State University, and Colorado State University previously. He is a Fellow of the American College of Cardiology (FACC) as well as Fellow of the American Institute for Medical and Biological Engineering (FAIMBE)
Cardiovascular Ultrasound is calling for submissions to our Collection on Artificial intelligence in echocardiography.
The integration of AI technologies into echocardiographic practice has already yielded significant breakthroughs, such as enhanced image quality, automated measurements, and improved diagnostic accuracy. These innovations not only streamline workflows but also empower clinicians to make more informed decisions, ultimately leading to better patient outcomes. As we continue to explore the potential of AI, we can anticipate even more transformative advances on the horizon. Future developments may include sophisticated algorithms capable of predicting cardiovascular events, personalized treatment plans based on real-time data analysis, and enhanced training tools for medical professionals. By fostering research in this dynamic field, we can unlock the full potential of echocardiography, ensuring it remains at the forefront of cardiovascular care.
We invite researchers to contribute to this special Collection. Topics of interest include but are not limited to:
- AI algorithms for image acquisition: current status and future directions
- Integration of AI in clinical workflows: what does it look like today
- Predictive modeling in cardiovascular health: reporting AI
- Automated echocardiographic measurements: interpretation AI
- Machine learning in diagnostic accuracy: clinical Decision-Making AI
- Challenges in Implementing AI in the Echo Lab
Image credit: © stock.adobe.com
There are currently no articles in this collection.
Articles for this Collection should be submitted via our submission system, Snapp. Please, select the appropriate Collection title “Artificial intelligence in echocardiography" under the “Details” tab during the submission stage.
Articles will undergo the journal’s standard peer-review process and are subject to all the journal’s standard policies. Articles will be added to the Collection as they are published.
The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.