Unsupervised machine learning improves risk stratification of patients with visual normal SPECT myocardial perfusion imaging assessments

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Unsupervised machine learning improves risk stratification of patients with visual normal SPECT myocardial perfusion imaging assessments

Session: New insights in nuclear cardiology

Topic: Single Photon Emission Computed Tomography (SPECT)

Event: ESC Congress 2022

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5 more presentations in this session

The Calcium Score's power of zero in 82-Rubidium PET depending on age group and sex

Speaker: Doctor S. Frey (Basel, CH)

Exploring macrophage mannose receptor expression after myocardial infarction by Al[18F]F-NOTA-DCM positron emission tomography

Speaker: Miss P. Andriana (Turku, FI)

Impaired cardiac sympathetic innervation activity is associated with myocardial extracellular remodeling, functional capacity and biomarkers

Speaker: Assistant Professor O. Coelho-Filho (Campinas, BR)

The discrepancy between FDG uptake and myocardial fibrosis in patients with pulmonary arterial hypertension - PET/MRI study.

Speaker: Doctor R. Kazimierczyk (Bialystok, PL)

18F-FDG-based radiomics and machine learning: a useful help for aortic prosthetic valve infective endocarditis diagnosis?

Speaker: Doctor T. Eugene (Nantes, FR)

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New insights in nuclear cardiology

Speakers: Doctor S. Frey, Miss P. Andriana, Assistant Professor O. Coelho-Filho, Doctor R. Kazimierczyk, Doctor T. Eugene

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ESC Congress 2022

26 August - 29 August 2022

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