Cargando…

Application of mobile health, telemedicine and artificial intelligence to echocardiography

The intersection of global broadband technology and miniaturized high-capability computing devices has led to a revolution in the delivery of healthcare and the birth of telemedicine and mobile health (mHealth). Rapid advances in handheld imaging devices with other mHealth devices such as smartphone...

Descripción completa

Detalles Bibliográficos
Autores principales: Seetharam, Karthik, Kagiyama, Nobuyuki, Sengupta, Partho P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bioscientifica Ltd 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6432977/
https://www.ncbi.nlm.nih.gov/pubmed/30844756
http://dx.doi.org/10.1530/ERP-18-0081
_version_ 1783406224792879104
author Seetharam, Karthik
Kagiyama, Nobuyuki
Sengupta, Partho P
author_facet Seetharam, Karthik
Kagiyama, Nobuyuki
Sengupta, Partho P
author_sort Seetharam, Karthik
collection PubMed
description The intersection of global broadband technology and miniaturized high-capability computing devices has led to a revolution in the delivery of healthcare and the birth of telemedicine and mobile health (mHealth). Rapid advances in handheld imaging devices with other mHealth devices such as smartphone apps and wearable devices are making great strides in the field of cardiovascular imaging like never before. Although these technologies offer a bright promise in cardiovascular imaging, it is far from straightforward. The massive data influx from telemedicine and mHealth including cardiovascular imaging supersedes the existing capabilities of current healthcare system and statistical software. Artificial intelligence with machine learning is the one and only way to navigate through this complex maze of the data influx through various approaches. Deep learning techniques are further expanding their role by image recognition and automated measurements. Artificial intelligence provides limitless opportunity to rigorously analyze data. As we move forward, the futures of mHealth, telemedicine and artificial intelligence are increasingly becoming intertwined to give rise to precision medicine.
format Online
Article
Text
id pubmed-6432977
institution National Center for Biotechnology Information
language English
publishDate 2019
publisher Bioscientifica Ltd
record_format MEDLINE/PubMed
spelling pubmed-64329772019-03-27 Application of mobile health, telemedicine and artificial intelligence to echocardiography Seetharam, Karthik Kagiyama, Nobuyuki Sengupta, Partho P Echo Res Pract Review The intersection of global broadband technology and miniaturized high-capability computing devices has led to a revolution in the delivery of healthcare and the birth of telemedicine and mobile health (mHealth). Rapid advances in handheld imaging devices with other mHealth devices such as smartphone apps and wearable devices are making great strides in the field of cardiovascular imaging like never before. Although these technologies offer a bright promise in cardiovascular imaging, it is far from straightforward. The massive data influx from telemedicine and mHealth including cardiovascular imaging supersedes the existing capabilities of current healthcare system and statistical software. Artificial intelligence with machine learning is the one and only way to navigate through this complex maze of the data influx through various approaches. Deep learning techniques are further expanding their role by image recognition and automated measurements. Artificial intelligence provides limitless opportunity to rigorously analyze data. As we move forward, the futures of mHealth, telemedicine and artificial intelligence are increasingly becoming intertwined to give rise to precision medicine. Bioscientifica Ltd 2019-02-20 /pmc/articles/PMC6432977/ /pubmed/30844756 http://dx.doi.org/10.1530/ERP-18-0081 Text en © 2019 The authors http://creativecommons.org/licenses/by-nc/4.0/ This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/) .
spellingShingle Review
Seetharam, Karthik
Kagiyama, Nobuyuki
Sengupta, Partho P
Application of mobile health, telemedicine and artificial intelligence to echocardiography
title Application of mobile health, telemedicine and artificial intelligence to echocardiography
title_full Application of mobile health, telemedicine and artificial intelligence to echocardiography
title_fullStr Application of mobile health, telemedicine and artificial intelligence to echocardiography
title_full_unstemmed Application of mobile health, telemedicine and artificial intelligence to echocardiography
title_short Application of mobile health, telemedicine and artificial intelligence to echocardiography
title_sort application of mobile health, telemedicine and artificial intelligence to echocardiography
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6432977/
https://www.ncbi.nlm.nih.gov/pubmed/30844756
http://dx.doi.org/10.1530/ERP-18-0081
work_keys_str_mv AT seetharamkarthik applicationofmobilehealthtelemedicineandartificialintelligencetoechocardiography
AT kagiyamanobuyuki applicationofmobilehealthtelemedicineandartificialintelligencetoechocardiography
AT senguptaparthop applicationofmobilehealthtelemedicineandartificialintelligencetoechocardiography