id	author	title	date	pages	extension	mime	words	sentences	flesch	summary	cache	txt
cord-328438-irjo0l4s	Krittanawong, Chayakrit	Integration of novel monitoring devices with machine learning technology for scalable cardiovascular management	2020-10-09		.txt	text/plain	10200	427	32	Advances in cardiovascular monitoring technologies, such as the use of ubiquitous mobile devices and the development of novel portable sensors with seamless wireless connectivity and machine learning algorithms that can provide specialist-level diagnosis in near real time, have the potential for a more personalized care. Machine learning is a rapidly developing branch of AI that has shown early promise for use in cardiovascular medicine 61 through the extraction of clinically relevant patterns from complex data, such as detecting myocardial ischaemia from cardiac CT images 62 and interpreting arrhythmias from wearable ECG monitors 33 . Machine learning technology ('deep learning') 60 has also been shown to improve the performance of shock advice algorithms in an automated external defibrillator 66 to predict the onset of ventricular arrhythmias with the use of an artificial neural network 67 and to predict the onset of sudden cardiac arrest within 72 h by incorporating heart rate variability parameters with vital sign data 68 .	./cache/cord-328438-irjo0l4s.txt	./txt/cord-328438-irjo0l4s.txt