Machine Learning and the Future of Cardiovascular Care: JACC State-of-the-Art Review
G Quer, R Arnaout, M Henne, R Arnaout - Journal of the American College …, 2021 - jacc.org
The role of physicians has always been to synthesize the data available to them to identify
diagnostic patterns that guide treatment and follow response. Today, increasingly …
diagnostic patterns that guide treatment and follow response. Today, increasingly …
Deep learning in medical imaging and radiation therapy
The goals of this review paper on deep learning (DL) in medical imaging and radiation
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
therapy are to (a) summarize what has been achieved to date;(b) identify common and …
[HTML][HTML] Artificial intelligence, machine learning and health systems
December 2018• Vol. 8 No. 2• 020303 2 www. jogh. org• doi: 10.7189/jogh. 08.020303
progress in this field is attributable to a subset of AI–machine learning and one family of …
progress in this field is attributable to a subset of AI–machine learning and one family of …
State-of-the-art deep learning in cardiovascular image analysis
Cardiovascular imaging is going to change substantially in the next decade, fueled by the
deep learning revolution. For medical professionals, it is important to keep track of these …
deep learning revolution. For medical professionals, it is important to keep track of these …
AI in health: state of the art, challenges, and future directions
F Wang, A Preininger - Yearbook of medical informatics, 2019 - thieme-connect.com
Introduction: Artificial intelligence (AI) technologies continue to attract interest from a broad
range of disciplines in recent years, including health. The increase in computer hardware …
range of disciplines in recent years, including health. The increase in computer hardware …
Applications of artificial intelligence in cardiovascular imaging
M Sermesant, H Delingette, H Cochet, P Jaïs… - Nature Reviews …, 2021 - nature.com
Research into artificial intelligence (AI) has made tremendous progress over the past
decade. In particular, the AI-powered analysis of images and signals has reached human …
decade. In particular, the AI-powered analysis of images and signals has reached human …
From machine learning to deep learning: Advances in scoring functions for protein–ligand docking
Molecule docking has been regarded as a routine tool for drug discovery, but its accuracy
highly depends on the reliability of scoring functions (SFs). With the rapid development of …
highly depends on the reliability of scoring functions (SFs). With the rapid development of …
[PDF][PDF] Descriptive analysis of machine learning and its application in healthcare
SS Gadde, VDR Kalli - Int J Comp Sci Trends Technol, 2020 - academia.edu
The dynamic world of big data in the healthcare sector characterized by huge numbers,
complexity, and speeds is also not suited to conventional research methods. Methods are …
complexity, and speeds is also not suited to conventional research methods. Methods are …
Deep learning for diagnosis of chronic myocardial infarction on nonenhanced cardiac cine MRI
Background Renal impairment is common in patients with coronary artery disease and, if
severe, late gadolinium enhancement (LGE) imaging for myocardial infarction (MI) …
severe, late gadolinium enhancement (LGE) imaging for myocardial infarction (MI) …
Deep learning in cardiology
P Bizopoulos, D Koutsouris - IEEE reviews in biomedical …, 2018 - ieeexplore.ieee.org
The medical field is creating large amount of data that physicians are unable to decipher
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …
and use efficiently. Moreover, rule-based expert systems are inefficient in solving …