Literature DB >> 35029816

The application of artificial intelligence in nuclear cardiology.

Yuka Otaki1,2, Robert J H Miller3,4, Piotr J Slomka3.   

Abstract

A decade of unprecedented progress in artificial intelligence (AI) has demonstrated a lot of interest in medical imaging research including nuclear cardiology. AI has a potential to reduce cost, save time and improve image acquisition, interpretation, and decision-making. This review summarizes recent researches and potential applications of AI in nuclear cardiology and discusses the pitfall of AI.
© 2021. The Author(s) under exclusive licence to The Japanese Society of Nuclear Medicine.

Entities:  

Keywords:  Artificial intelligence; Deep learning; Machine learning; Nuclear cardiology; SPECT

Mesh：

Year:  2022        PMID： 35029816     DOI： 10.1007/s12149-021-01708-2

Source DB:  PubMed          Journal:  Ann Nucl Med        ISSN： 0914-7187            Impact factor:   2.668


  3 in total

1.  Integration of automatically measured transient ischemic dilation ratio into interpretation of adenosine stress myocardial perfusion SPECT for detection of severe and extensive CAD.

Authors:  Aiden Abidov; Jeroen J Bax; Sean W Hayes; Ishac Cohen; Hidetaka Nishina; Shunichi Yoda; Xingping Kang; Fatma Aboul-Enein; James Gerlach; John D Friedman; Rory Hachamovitch; Guido Germano; Daniel S Berman
Journal:  J Nucl Med       Date:  2004-12       Impact factor: 10.057

2.  Prediction of myocardial infarction versus cardiac death by gated myocardial perfusion SPECT: risk stratification by the amount of stress-induced ischemia and the poststress ejection fraction.

Authors:  T Sharir; G Germano; X Kang; H C Lewin; R Miranda; I Cohen; R D Agafitei; J D Friedman; D S Berman
Journal:  J Nucl Med       Date:  2001-06       Impact factor: 10.057

3.  Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis.

Authors:  Manish Motwani; Damini Dey; Daniel S Berman; Guido Germano; Stephan Achenbach; Mouaz H Al-Mallah; Daniele Andreini; Matthew J Budoff; Filippo Cademartiri; Tracy Q Callister; Hyuk-Jae Chang; Kavitha Chinnaiyan; Benjamin J W Chow; Ricardo C Cury; Augustin Delago; Millie Gomez; Heidi Gransar; Martin Hadamitzky; Joerg Hausleiter; Niree Hindoyan; Gudrun Feuchtner; Philipp A Kaufmann; Yong-Jin Kim; Jonathon Leipsic; Fay Y Lin; Erica Maffei; Hugo Marques; Gianluca Pontone; Gilbert Raff; Ronen Rubinshtein; Leslee J Shaw; Julia Stehli; Todd C Villines; Allison Dunning; James K Min; Piotr J Slomka
Journal:  Eur Heart J       Date:  2017-02-14       Impact factor: 29.983
  3 in total
  2 in total

1.  Statistical methods for validation of predictive models.

Authors:  Marcio Augusto Diniz
Journal:  J Nucl Cardiol       Date:  2022-05-24       Impact factor: 5.952

2.  Diagnosis of Parkinson syndrome and Lewy-body disease using 123I-ioflupane images and a model with image features based on machine learning.

Authors:  Kenichi Nakajima; Shintaro Saito; Zhuoqing Chen; Junji Komatsu; Koji Maruyama; Naoki Shirasaki; Satoru Watanabe; Anri Inaki; Kenjiro Ono; Seigo Kinuya
Journal:  Ann Nucl Med       Date:  2022-07-07       Impact factor: 2.258
  2 in total

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