Literature DB >> 32648059

Radiomics in Echocardiography: Deep Learning and Echocardiographic Analysis.

Kenya Kusunose1.   

Abstract

PURPOSE OF REVIEW: Recent development in artificial intelligence (AI) for cardiovascular imaging analysis, involving deep learning, is the start of a new phase in the research field. We review the current state of AI in cardiovascular field and discuss about its potential to improve clinical workflows and accuracy of diagnosis. RECENT
FINDINGS: In the AI cardiovascular imaging field, there are many applications involving efficient image reconstruction, patient triage, and support for clinical decisions. These tools have a role to support repetitive clinical tasks. Although they will be powerful in some situations, these applications may have new potential in the hands of echo cardiologists, assisting but not replacing the human observer. We believe AI has the potential to improve the quality of echocardiography. Someday AI may be incorporated into the daily clinical setting, being an instrumental tool for cardiologists dealing with cardiovascular diseases.

Entities:  

Keywords:  Artificial intelligence; Automated diagnosis; Deep learning; Echocardiography; Machine learning; Myocardial infarction

Mesh:

Year:  2020        PMID: 32648059     DOI: 10.1007/s11886-020-01348-4

Source DB:  PubMed          Journal:  Curr Cardiol Rep        ISSN: 1523-3782            Impact factor:   2.931


  1 in total

1.  Novel Hypertrophic Cardiomyopathy Diagnosis Index Using Deep Features and Local Directional Pattern Techniques.

Authors:  Anjan Gudigar; U Raghavendra; Jyothi Samanth; Chinmay Dharmik; Mokshagna Rohit Gangavarapu; Krishnananda Nayak; Edward J Ciaccio; Ru-San Tan; Filippo Molinari; U Rajendra Acharya
Journal:  J Imaging       Date:  2022-04-06
  1 in total

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