Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Aug 1, 2022
BACKGROUND: Studies have shown that the conventional parameters characterizing left ventricular mechanical dyssynchrony (LVMD) measured on gated SPECT myocardial perfusion imaging (MPI) have their own statistical limitations in predicting cardiac res...
BACKGROUND: Although risk stratification of patients with acute decompensated heart failure (HF) is important, it is unknown whether machine learning (ML) or conventional statistical models are optimal. We developed ML algorithms to predict 7-day and...
BACKGROUND: Surgical mechanical ventricular assistance and cardiac replacement therapies, although life-saving in many heart failure (HF) patients, remain high-risk. Despite this, the difficulty in timely identification of medical therapy nonresponde...
Dilated cardiomyopathy (DCM) is characterized by reduced cardiac output, as well as thinning and enlargement of left ventricular chambers. These characteristics eventually lead to heart failure. Current standards of care do not target the underlying ...
IEEE journal of biomedical and health informatics
Jul 1, 2022
Predicting the incidence of complex chronic conditions such as heart failure is challenging. Deep learning models applied to rich electronic health records may improve prediction but remain unexplainable hampering their wider use in medical practice....
AIMS: Risk changes with the progression of disease and the impact of treatment. We developed a dynamic risk stratification Markov chain model using artificial intelligence in patients with chronic heart failure (CHF).
AIMS: Prognostic enrichment strategies can make trials more efficient, although potentially at the cost of diminishing external validity. Whether using a risk score to identify a population at increased mortality risk could improve trial efficiency i...
Journal of ultrasound in medicine : official journal of the American Institute of Ultrasound in Medicine
May 12, 2022
OBJECTIVES: To test if a deep learning (DL) model trained on echocardiography images could accurately segment the left ventricle (LV) and predict ejection fraction on apical 4-chamber images acquired by point-of-care ultrasound (POCUS).
We present a novel multimodal deep learning framework for cardiac resynchronisation therapy (CRT) response prediction from 2D echocardiography and cardiac magnetic resonance (CMR) data. The proposed method first uses the 'nnU-Net' segmentation model ...
Advancements in technology have improved biomarker discovery in the field of heart failure (HF). What was once a slow and laborious process has gained efficiency through use of high-throughput omics platforms to phenotype HF at the level of genes, tr...
Join thousands of healthcare professionals staying informed about the latest AI breakthroughs in medicine. Get curated insights delivered to your inbox.