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充血性心力衰竭

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Natriuretic Peptide-Guided Heart Failure Therapy After the GUIDE-IT Study Primary Prevention of Heart Failure in Women Is Acute heart failure a distinctive disorder? An analysis from BIOSTAT-CHF Unexpectedly Low Natriuretic Peptide Levels in Patients With Heart Failure In acute HF and iron deficiency, IV ferric carboxymaltose reduced HF hospitalizations, but not CV death, at 1 y Nuclear Imaging of the Cardiac Sympathetic Nervous System: A Disease-Specific Interpretation in Heart Failure The pyruvate-lactate axis modulates cardiac hypertrophy and heart failure Heart Failure Outcomes With Volume-Guided Management SPECT and PET in ischemic heart failure Clinical applications of machine learning in the diagnosis, classification, and prediction of heart failure

Review Article2020 Jul 16;229:1-17.

JOURNAL:Am Heart J . Article Link

Clinical applications of machine learning in the diagnosis, classification, and prediction of heart failure

CR Olsen, RJ Mentz, KJ Anstrom et al. Keywords: machine learning; artificial intelligence;

ABSTRACT

Machine learning and artificial intelligence are generating significant attention in the scientific community and media. Such algorithms have great potential in medicine for personalizing and improving patient care, including in the diagnosis and management of heart failure. Many physicians are familiar with these terms and the excitement surrounding them, but many are unfamiliar with the basics of these algorithms and how they are applied to medicine. Within heart failure research, current applications of machine learning include creating new approaches to diagnosis, classifying patients into novel phenotypic groups, and improving prediction capabilities. In this paper, we provide an overview of machine learning targeted for the practicing clinician and evaluate current applications of machine learning in the diagnosis, classification, and prediction of heart failure.