Authors :
Usha Topalkatti; Bhagyaraju Koppu; Ram Chandra Prasad; Kalva Suchitra Reddy
Volume/Issue :
Volume 8 - 2023, Issue 7 - July
Google Scholar :
https://bit.ly/3TmGbDi
Scribd :
https://tinyurl.com/muy2fj5r
DOI :
https://doi.org/10.5281/zenodo.8163685
Abstract :
Recent advancements made in artificial
intelligence (AI) and machine learning (ML) technology
in cardiology and echocardiography has significant
importance to revolutionising diagnosis. AI has potential
to assist in detecting, classifying, diagnosing, and
prognosticating cardiac abnormalities in terms of
improved workflow efficiency, reproducibility, and
diagnostic accuracy. It offers cost-effecti solution to meet
the increasing demand for cardiac imaging. However,
several challenges need to be addressed before AI can be
widely adopted in clinical practice. These challenges
include the need for more data on AI and clinical
outcomes and the validation of AI models through
prospective studies. Overcoming these obstacles through
further research will unlock full potential of AI in
cardiology and echocardiography, ultimately enhancing
medical care.
Keywords :
Artificial Intelligence, Cardiology, Echocardiography, Diagnostic Accuracy, Heart Failure, Diagnosis
Recent advancements made in artificial
intelligence (AI) and machine learning (ML) technology
in cardiology and echocardiography has significant
importance to revolutionising diagnosis. AI has potential
to assist in detecting, classifying, diagnosing, and
prognosticating cardiac abnormalities in terms of
improved workflow efficiency, reproducibility, and
diagnostic accuracy. It offers cost-effecti solution to meet
the increasing demand for cardiac imaging. However,
several challenges need to be addressed before AI can be
widely adopted in clinical practice. These challenges
include the need for more data on AI and clinical
outcomes and the validation of AI models through
prospective studies. Overcoming these obstacles through
further research will unlock full potential of AI in
cardiology and echocardiography, ultimately enhancing
medical care.
Keywords :
Artificial Intelligence, Cardiology, Echocardiography, Diagnostic Accuracy, Heart Failure, Diagnosis
