Clinical applications of artificial intelligence—an updated overview

Ș Busnatu, AG Niculescu, A Bolocan… - Journal of clinical …, 2022 - mdpi.com
Artificial intelligence has the potential to revolutionize modern society in all its aspects.
Encouraged by the variety and vast amount of data that can be gathered from patients (eg …

Transfer learning for non-image data in clinical research: a sco** review

A Ebbehoj, MØ Thunbo, OE Andersen… - PLOS Digital …, 2022 - journals.plos.org
Background Transfer learning is a form of machine learning where a pre-trained model
trained on a specific task is reused as a starting point and tailored to another task in a …

Severe aortic stenosis detection by deep learning applied to echocardiography

G Holste, EK Oikonomou, BJ Mortazavi… - European Heart …, 2023 - academic.oup.com
Abstract Background and Aims Early diagnosis of aortic stenosis (AS) is critical to prevent
morbidity and mortality but requires skilled examination with Doppler imaging. This study …

[HTML][HTML] Artificial intelligence for detection of cardiovascular-related diseases from wearable devices: a systematic review and meta-analysis

S Lee, Y Chu, J Ryu, YJ Park, S Yang… - Yonsei medical …, 2022 - ncbi.nlm.nih.gov
Purpose Several artificial intelligence (AI) models for the detection and prediction of
cardiovascular-related diseases, including arrhythmias, diabetes, and sleep apnea, have …

Efficient detection of aortic stenosis using morphological characteristics of cardiomechanical signals and heart rate variability parameters

A Shokouhmand, ND Aranoff, E Driggin, P Green… - Scientific reports, 2021 - nature.com
Recent research has shown promising results for the detection of aortic stenosis (AS) using
cardio-mechanical signals. However, they are limited by two main factors: lacking physical …

A primer on the present state and future prospects for machine learning and artificial intelligence applications in cardiology

C Manlhiot, J van den Eynde, S Kutty… - Canadian Journal of …, 2022 - Elsevier
The artificial intelligence (AI) revolution is well underway, including in the medical field, and
has dramatically transformed our lives. An understanding of the basics of AI applications …

A new semi-supervised learning benchmark for classifying view and diagnosing aortic stenosis from echocardiograms

Z Huang, G Long, B Wessler… - Machine Learning for …, 2021 - proceedings.mlr.press
Semi-supervised image classification has shown substantial progress in learning from
limited labeled data, but recent advances remain largely untested for clinical applications …

Successfully implemented artificial intelligence and machine learning applications in cardiology: state-of-the-art review

J Van den Eynde, M Lachmann, KL Laugwitz… - Trends in cardiovascular …, 2023 - Elsevier
The omnipresence and deep impact of artificial intelligence (AI) in today's society are
undeniable. While the technology has already established itself as a powerful tool in several …

Machine learning to optimize the echocardiographic follow-up of aortic stenosis

A Sánchez-Puente, PI Dorado-Díaz… - Cardiovascular …, 2023 - jacc.org
Background Disease progression in patients with mild-to-moderate aortic stenosis is
heterogenous and requires periodic echocardiographic examinations to evaluate severity …

M2ECG: Wearable mechanocardiograms to electrocardiogram estimation using deep learning

MI Tapotee, P Saha, S Mahmud, A Alqahtani… - IEEE …, 2024 - ieeexplore.ieee.org
Chest surface vibrations induced by cardiac activities can provide valuable insights into
various heart conditions. Seismocardiogram (SCG) and Gyrocardiogram (GCG) signals …