[HTML][HTML] Digital transformation in the diagnostics and therapy of cardiovascular diseases: comprehensive literature review

C Stremmel, R Breitschwerdt - JMIR cardio, 2023 - cardio.jmir.org
Background: The digital transformation of our health care system has experienced a clear
shift in the last few years due to political, medical, and technical innovations and …

Interpretable machine learning for 28-day all-cause in-hospital mortality prediction in critically ill patients with heart failure combined with hypertension: A retrospective …

S Peng, J Huang, X Liu, J Deng, C Sun… - Frontiers in …, 2022 - frontiersin.org
Background Heart failure (HF) combined with hypertension is an extremely important cause
of in-hospital mortality, especially for the intensive care unit (ICU) patients. However, under …

Development of deep-learning models for real-time anaerobic threshold and peak VO2 prediction during cardiopulmonary exercise testing

T Watanabe, T Tohyama, M Ikeda… - European Journal of …, 2024 - academic.oup.com
Aims Exercise intolerance is a clinical feature of patients with heart failure (HF).
Cardiopulmonary exercise testing (CPET) is the first-line examination for assessing exercise …

Cardiac autoantibodies against cardiac troponin I in post-myocardial infarction heart failure: evaluation in a novel murine model and applications in therapeutics

S Furusawa, M Ikeda, T Ide, T Kanamura… - Circulation: Heart …, 2023 - Am Heart Assoc
BACKGROUND: Cardiac autoantibodies (cAAbs) are involved in the progression of adverse
cardiac remodeling in heart failure (HF). However, our understanding of cAAbs in HF is …

Application of machine learning in predicting frailty syndrome in patients with heart failure

R Szczepanowski, I Uchmanowicz… - Advances in Clinical …, 2024 - pure.qub.ac.uk
Prevention and diagnosis of frailty syndrome (FS) in patients with heart failure (HF) require
innovative systems to help medical personnel tailor and optimize their treatment and care …

[HTML][HTML] Outcomes and predictors of one-year mortality in patients hospitalized with Acute Heart Failure

K Lorlowhakarn, S Arayakarnkul, A Trongtorsak… - IJC Heart & …, 2022 - Elsevier
Background Registries of patients hospitalized with acute heart failure (AHF) provided useful
description of characteristics and outcomes. However, a contemporary registry which …

Predicting long-term mortality in patients with acute heart failure by using machine learning

J Park, IC Hwang, YE Yoon, JB Park, JH Park… - Journal of Cardiac …, 2022 - Elsevier
Background High mortality rates in patients with acute heart failure (AHF) necessitate proper
risk stratification. However, risk-assessment tools for long-term mortality are largely lacking …

Machine learning prediction of atrial fibrillation in cardiovascular patients using cardiac magnetic resonance and electronic health information

S Dykstra, A Satriano, AK Cornhill, LY Lei… - Frontiers in …, 2022 - frontiersin.org
Background Atrial fibrillation (AF) is a commonly encountered cardiac arrhythmia associated
with morbidity and substantial healthcare costs. While patients with cardiovascular disease …

[HTML][HTML] Representation of time-varying and time-invariant EMR data and its application in modeling outcome prediction for heart failure patients

Y Huang, M Wang, Z Zheng, M Ma, X Fei, L Wei… - Journal of Biomedical …, 2023 - Elsevier
Objective To represent a patient record with both time-invariant and time-varying features as
a single vector using an end-to-end deep learning model, and further to predict the kidney …

Differences in clinical outcomes between octogenarian and nonagenarian patients with acute heart failure

K Sakaguchi, Y Uemura, R Shibata… - Geriatrics & …, 2023 - Wiley Online Library
Aim The number of hospitalized super‐elderly patients with heart failure (HF) has increased
with aging of the population. These patients are associated with poor clinical outcomes with …