Broadening Perspectives of Artificial Intelligence in Echocardiography.
Karthik SeetharamHarshith ThyagaturuGabriel Lora FerreiraAditya PatelChinmay PatelAsim ElahiRoman PachulskiJilan ShahParvez MirArunita ThodimelaManya PalaZeyar ThetYasmin HamiraniPublished in: Cardiology and therapy (2024)
Echocardiography frequently serves as the first-line treatment of diagnostic imaging for several pathological entities in cardiology. Artificial intelligence (AI) has been growing substantially in information technology and various commercial industries. Machine learning (ML), a branch of AI, has been shown to expand the capabilities and potential of echocardiography. ML algorithms expand the field of echocardiography by automated assessment of the ejection fraction and left ventricular function, integrating novel approaches such as speckle tracking or tissue Doppler echocardiography or vector flow mapping, improved phenotyping, distinguishing between cardiac conditions, and incorporating information from mobile health and genomics. In this review article, we assess the impact of AI and ML in echocardiography.
Keyphrases
- artificial intelligence
- left ventricular
- machine learning
- deep learning
- big data
- aortic stenosis
- pulmonary hypertension
- computed tomography
- hypertrophic cardiomyopathy
- ejection fraction
- acute myocardial infarction
- heart failure
- cardiac resynchronization therapy
- left atrial
- mitral valve
- high resolution
- cardiac surgery
- acute kidney injury
- high throughput
- climate change
- blood flow
- percutaneous coronary intervention
- mass spectrometry