Clinical applications of machine learning in the diagnosis, classification, and prediction of heart failure
Abstract Machine learning and artificial intelligence are generating significant attention in
the scientific community and media. Such algorithms have great potential in medicine for …
the scientific community and media. Such algorithms have great potential in medicine for …
Artificial intelligence and heart failure: A state‐of‐the‐art review
Heart failure (HF) is a heterogeneous syndrome affecting more than 60 million individuals
globally. Despite recent advancements in understanding of the pathophysiology of HF, many …
globally. Despite recent advancements in understanding of the pathophysiology of HF, many …
[HTML][HTML] Left ventricular assist systems and infection-related outcomes: a comprehensive analysis of the MOMENTUM 3 trial
CB Patel, L Blue, B Cagliostro, SH Bailey… - The Journal of Heart and …, 2020 - Elsevier
BACKGROUND In a randomized controlled trial (MOMENTUM 3), the HeartMate 3 (HM3)
fully magnetically levitated centrifugal-flow left ventricular assist device (LVAD) …
fully magnetically levitated centrifugal-flow left ventricular assist device (LVAD) …
Developing machine learning models for prediction of mortality in the medical intensive care unit
B Nistal-Nuño - Computer Methods and Programs in Biomedicine, 2022 - Elsevier
Background and objective Alert of patient deterioration is essential for prompt medical
intervention in the Medical Intensive Care Unit (MICU). Logistic Regression (LR) has been …
intervention in the Medical Intensive Care Unit (MICU). Logistic Regression (LR) has been …
Long-term survival on LVAD support: device complications and end-organ dysfunction limit long-term success
IM Hariri, T Dardas, M Kanwar, R Cogswell… - The Journal of Heart and …, 2022 - Elsevier
Background Preoperative variables can predict short term left ventricular assist device
(LVAD) survival, but predictors of extended survival remain insufficiently characterized …
(LVAD) survival, but predictors of extended survival remain insufficiently characterized …
Contemporary applications of machine learning for device therapy in heart failure
Despite a better understanding of the underlying pathogenesis of heart failure (HF),
pharmacotherapy, surgical, and percutaneous interventions do not prevent disease …
pharmacotherapy, surgical, and percutaneous interventions do not prevent disease …
[HTML][HTML] Center variability in patient outcomes following HeartMate 3 implantation: an analysis of the MOMENTUM 3 trial
Background As left ventricular assist device (LVAD) survival rates continue to improve,
evaluating site-specific variability in outcomes can facilitate identifying targets for quality …
evaluating site-specific variability in outcomes can facilitate identifying targets for quality …
The Role of Artificial Intelligence and Machine Learning in the Prediction of Right Heart Failure after Left Ventricular Assist Device Implantation: A Comprehensive …
One of the most challenging and prevalent side effects of LVAD implantation is that of right
heart failure (RHF) that may develop afterwards. The purpose of this study is to review and …
heart failure (RHF) that may develop afterwards. The purpose of this study is to review and …
[HTML][HTML] Prediction of algal bloom occurrence based on the naive Bayesian model considering satellite image pixel differences
Bloom occurrence probability prediction is a critical issue for freshwater resource
management and protection. As the mechanism of algal blooms is not understood, the …
management and protection. As the mechanism of algal blooms is not understood, the …
Bayesian network as a decision tool for predicting ALS disease
Clinical diagnosis of amyotrophic lateral sclerosis (ALS) is difficult in the early period. But
blood tests are less time consuming and low cost methods compared to other methods for …
blood tests are less time consuming and low cost methods compared to other methods for …