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The incidence of Heart failure with preserved ejection fraction (HFpEF) in Heart failure patients increases rapidly. However, the current clinical awareness is insufficient, and the cardiac structural and functional injury are not well understood. It is difficult to recognize the subclinical changes of the cardiac in the early stage with conventional imaging techniques, and it is common to ignore the existence of the clinical alterations. This study aimed to investigate the cardiac features, early diagnosis and risk factors of HFpEF patients, based on the multi-modal (Magnetic resonance imaging- nuclear medicine imaging- echocardiography) imaging, combined with large data and artificial intelligence. This study will provide deep insights into the HFpEF derived from different causes.
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