Clinical applications of machine learning in cardiovascular disease and its relevance to cardiac imaging

SJ Al'Aref, K Anchouche, G Singh… - European heart …, 2019 - academic.oup.com
Artificial intelligence (AI) has transformed key aspects of human life. Machine learning (ML),
which is a subset of AI wherein machines autonomously acquire information by extracting …

Artificial intelligence in cardiology: Hope for the future and power for the present

L Karatzia, N Aung, D Aksentijevic - Frontiers in Cardiovascular …, 2022 - frontiersin.org
Cardiovascular disease (CVD) is the principal cause of mortality and morbidity globally. With
the pressures for improved care and translation of the latest medical advances and …

[HTML][HTML] CT​ evaluation​ by​ artificial​ intelligence​ for​ atherosclerosis, stenosis and vascular​ morphology​(CLARIFY):​ a​ multi-center, international study

AD Choi, H Marques, V Kumar, WF Griffin… - Journal of …, 2021 - Elsevier
Background Atherosclerosis evaluation by coronary computed tomography angiography
(CCTA) is promising for coronary artery disease (CAD) risk stratification, but time consuming …

Machine learning of clinical variables and coronary artery calcium scoring for the prediction of obstructive coronary artery disease on coronary computed tomography …

SJ Al'Aref, G Maliakal, G Singh… - European heart …, 2020 - academic.oup.com
Aims Symptom-based pretest probability scores that estimate the likelihood of obstructive
coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to …

Artificial intelligence, machine learning, and cardiovascular disease

P Mathur, S Srivastava, X Xu… - Clinical Medicine …, 2020 - journals.sagepub.com
Artificial intelligence (AI)-based applications have found widespread applications in many
fields of science, technology, and medicine. The use of enhanced computing power of …

Myocardial infarction associates with a distinct pericoronary adipose tissue radiomic phenotype: a prospective case-control study

A Lin, M Kolossváry, J Yuvaraj, S Cadet… - Cardiovascular …, 2020 - jacc.org
Objectives This study sought to determine whether coronary computed tomography
angiography (CCTA)-based radiomic analysis of pericoronary adipose tissue (PCAT) could …

Long-COVID diagnosis: From diagnostic to advanced AI-driven models

R Cau, G Faa, V Nardi, A Balestrieri, J Puig… - European journal of …, 2022 - Elsevier
SARS-COV 2 is recognized to be responsible for a multi-organ syndrome. In most patients,
symptoms are mild. However, in certain subjects, COVID-19 tends to progress more …

Machine learning to predict the long-term risk of myocardial infarction and cardiac death based on clinical risk, coronary calcium, and epicardial adipose tissue: a …

F Commandeur, PJ Slomka, M Goeller… - Cardiovascular …, 2020 - academic.oup.com
Aims Our aim was to evaluate the performance of machine learning (ML), integrating clinical
parameters with coronary artery calcium (CAC), and automated epicardial adipose tissue …

Artificial intelligence in cardiac radiology

M van Assen, G Muscogiuri, D Caruso, SJ Lee… - La radiologia …, 2020 - Springer
Artificial intelligence (AI) is entering the clinical arena, and in the early stage, its
implementation will be focused on the automatization tasks, improving diagnostic accuracy …

Artificial intelligence and machine learning in radiology: current state and considerations for routine clinical implementation

JL Wichmann, MJ Willemink… - Investigative …, 2020 - journals.lww.com
Although artificial intelligence (AI) has been a focus of medical research for decades, in the
last decade, the field of radiology has seen tremendous innovation and also public focus …