“Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review

Sentiment Analysis (SA) is a novel branch of Natural Language Processing (NLP) that measures emotions or attitudes behind a written text. First applications of SA in healthcare were the detection of disease-related emotional polarities in social media. Now it is possible to extract more complex atti...
Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Adrian Brezulianu [verfasserIn] Alexandru Burlacu [verfasserIn] Iolanda Valentina Popa [verfasserIn] Muhammad Arif [verfasserIn] Oana Geman [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2022

Schlagwörter:	sentiment analysis cardiovascular artificial intelligence machine learning social media

Übergeordnetes Werk:	In: Frontiers in Public Health - Frontiers Media S.A., 2013, 10(2022)
Übergeordnetes Werk:	volume:10 ; year:2022

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.3389/fpubh.2022.880207

Katalog-ID:	DOAJ059128674

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allfieldsSound	10.3389/fpubh.2022.880207 doi (DE-627)DOAJ059128674 (DE-599)DOAJ9fdc3cab62ce4ef7a5470b6c8b150470 DE-627 ger DE-627 rakwb eng RA1-1270 Adrian Brezulianu verfasserin aut “Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review 2022 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Sentiment Analysis (SA) is a novel branch of Natural Language Processing (NLP) that measures emotions or attitudes behind a written text. First applications of SA in healthcare were the detection of disease-related emotional polarities in social media. Now it is possible to extract more complex attitudes (rank attitudes from 1 to 5, assign appraisal values, apply multiple text classifiers) or feelings through NLP techniques, with clear benefits in cardiology; as emotions were proved to be veritable risk factors for the development of cardiovascular diseases (CVD). Our narrative review aimed to summarize the current directions of SA in cardiology and raise the awareness of cardiologists about the potentiality of this novel domain. This paper introduces the readers to basic concepts surrounding medical SA and the need for SA in cardiovascular healthcare. Our synthesis of the current literature proved SA's clinical potential in CVD. However, many other clinical utilities, such as the assessment of emotional consequences of illness, patient-physician relationship, physician intuitions in CVD are not yet explored. These issues constitute future research directions, along with proposing detailed regulations, popularizing health social media among elders, developing insightful definitions of emotional polarity, and investing research into the development of powerful SA algorithms. sentiment analysis cardiovascular artificial intelligence machine learning social media Public aspects of medicine Adrian Brezulianu verfasserin aut Alexandru Burlacu verfasserin aut Alexandru Burlacu verfasserin aut Iolanda Valentina Popa verfasserin aut Iolanda Valentina Popa verfasserin aut Muhammad Arif verfasserin aut Oana Geman verfasserin aut In Frontiers in Public Health Frontiers Media S.A., 2013 10(2022) (DE-627)742224589 (DE-600)2711781-9 22962565 nnns volume:10 year:2022 https://doi.org/10.3389/fpubh.2022.880207 kostenfrei https://doaj.org/article/9fdc3cab62ce4ef7a5470b6c8b150470 kostenfrei https://www.frontiersin.org/articles/10.3389/fpubh.2022.880207/full kostenfrei https://doaj.org/toc/2296-2565 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ SSG-OLC-PHA GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_206 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_602 GBV_ILN_2003 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 10 2022
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callnumber-first	R - Medicine
author	Adrian Brezulianu
spellingShingle	Adrian Brezulianu misc RA1-1270 misc sentiment analysis misc cardiovascular misc artificial intelligence misc machine learning misc social media misc Public aspects of medicine “Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review
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topic_title	RA1-1270 “Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review sentiment analysis cardiovascular artificial intelligence machine learning social media
topic	misc RA1-1270 misc sentiment analysis misc cardiovascular misc artificial intelligence misc machine learning misc social media misc Public aspects of medicine
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title	“Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review
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title_full	“Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review
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title_sort	“not by our feeling, but by other's seeing”: sentiment analysis technique in cardiology—an exploratory review
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title_auth	“Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review
abstract	Sentiment Analysis (SA) is a novel branch of Natural Language Processing (NLP) that measures emotions or attitudes behind a written text. First applications of SA in healthcare were the detection of disease-related emotional polarities in social media. Now it is possible to extract more complex attitudes (rank attitudes from 1 to 5, assign appraisal values, apply multiple text classifiers) or feelings through NLP techniques, with clear benefits in cardiology; as emotions were proved to be veritable risk factors for the development of cardiovascular diseases (CVD). Our narrative review aimed to summarize the current directions of SA in cardiology and raise the awareness of cardiologists about the potentiality of this novel domain. This paper introduces the readers to basic concepts surrounding medical SA and the need for SA in cardiovascular healthcare. Our synthesis of the current literature proved SA's clinical potential in CVD. However, many other clinical utilities, such as the assessment of emotional consequences of illness, patient-physician relationship, physician intuitions in CVD are not yet explored. These issues constitute future research directions, along with proposing detailed regulations, popularizing health social media among elders, developing insightful definitions of emotional polarity, and investing research into the development of powerful SA algorithms.
abstractGer	Sentiment Analysis (SA) is a novel branch of Natural Language Processing (NLP) that measures emotions or attitudes behind a written text. First applications of SA in healthcare were the detection of disease-related emotional polarities in social media. Now it is possible to extract more complex attitudes (rank attitudes from 1 to 5, assign appraisal values, apply multiple text classifiers) or feelings through NLP techniques, with clear benefits in cardiology; as emotions were proved to be veritable risk factors for the development of cardiovascular diseases (CVD). Our narrative review aimed to summarize the current directions of SA in cardiology and raise the awareness of cardiologists about the potentiality of this novel domain. This paper introduces the readers to basic concepts surrounding medical SA and the need for SA in cardiovascular healthcare. Our synthesis of the current literature proved SA's clinical potential in CVD. However, many other clinical utilities, such as the assessment of emotional consequences of illness, patient-physician relationship, physician intuitions in CVD are not yet explored. These issues constitute future research directions, along with proposing detailed regulations, popularizing health social media among elders, developing insightful definitions of emotional polarity, and investing research into the development of powerful SA algorithms.
abstract_unstemmed	Sentiment Analysis (SA) is a novel branch of Natural Language Processing (NLP) that measures emotions or attitudes behind a written text. First applications of SA in healthcare were the detection of disease-related emotional polarities in social media. Now it is possible to extract more complex attitudes (rank attitudes from 1 to 5, assign appraisal values, apply multiple text classifiers) or feelings through NLP techniques, with clear benefits in cardiology; as emotions were proved to be veritable risk factors for the development of cardiovascular diseases (CVD). Our narrative review aimed to summarize the current directions of SA in cardiology and raise the awareness of cardiologists about the potentiality of this novel domain. This paper introduces the readers to basic concepts surrounding medical SA and the need for SA in cardiovascular healthcare. Our synthesis of the current literature proved SA's clinical potential in CVD. However, many other clinical utilities, such as the assessment of emotional consequences of illness, patient-physician relationship, physician intuitions in CVD are not yet explored. These issues constitute future research directions, along with proposing detailed regulations, popularizing health social media among elders, developing insightful definitions of emotional polarity, and investing research into the development of powerful SA algorithms.
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title_short	“Not by Our Feeling, But by Other's Seeing”: Sentiment Analysis Technique in Cardiology—An Exploratory Review
url	https://doi.org/10.3389/fpubh.2022.880207 https://doaj.org/article/9fdc3cab62ce4ef7a5470b6c8b150470 https://www.frontiersin.org/articles/10.3389/fpubh.2022.880207/full https://doaj.org/toc/2296-2565
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up_date	2024-07-03T21:55:59.911Z
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