ANFIS Models for Heart Disease Prediction

Siyue Song; Tianhua Chen; Grigoris Antoniou

doi:10.1145/3461353.3461354

ANFIS Models for Heart Disease Prediction

Siyue Song, Tianhua Chen, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

1 Citation (Scopus)

Abstract

Coronary heart disease is the one of the most common diseases and a major cause of death internationally. The early detection and prediction of such disease is thus very important for human life. Currently, the Adaptive Neural Fuzzy Inference System (ANFIS) is increasingly becoming popular in the field of prediction and diagnosis of medical disease, because ANFIS can arrive at the definite conclusion by dealing with ambiguous, imprecise and vague information in activities or processes. This paper reviews the application of ANFIS in the field of heart disease prediction, as well as some innovative combinations of ANFIS and other techniques for clinical decision support on heart disease diagnosis. Finally, we identify ideas for future work aiming to improve ANFIS model.

Original language	English
Title of host publication	ICIAI 2021- 5th International Conference on Innovation in Artificial Intelligence
Subtitle of host publication	(ICIAI 2021)
Place of Publication	New York
Publisher	Association for Computing Machinery (ACM)
Pages	32-35
Number of pages	4
ISBN (Electronic)	9781450388634
ISBN (Print)	9781450388634
DOIs	https://doi.org/10.1145/3461353.3461354
Publication status	Published - 5 Mar 2021
Event	5th International Conference on Innovation in Artificial Intelligence - Due to take place Xiamen China but held virtually due to COVID 19, Virtual Duration: 5 Mar 2021 → 8 Mar 2021 Conference number: 5 http://www.iciai.org/

Publication series

Name	ACM International Conference Proceeding Series
Volume	PartF171546

Conference

Conference	5th International Conference on Innovation in Artificial Intelligence
Abbreviated title	ICIAI 2021
City	Virtual
Period	5/03/21 → 8/03/21
Internet address	http://www.iciai.org/

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This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1145/3461353.3461354Licence: Unspecified

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title = "ANFIS Models for Heart Disease Prediction",

abstract = "Coronary heart disease is the one of the most common diseases and a major cause of death internationally. The early detection and prediction of such disease is thus very important for human life. Currently, the Adaptive Neural Fuzzy Inference System (ANFIS) is increasingly becoming popular in the field of prediction and diagnosis of medical disease, because ANFIS can arrive at the definite conclusion by dealing with ambiguous, imprecise and vague information in activities or processes. This paper reviews the application of ANFIS in the field of heart disease prediction, as well as some innovative combinations of ANFIS and other techniques for clinical decision support on heart disease diagnosis. Finally, we identify ideas for future work aiming to improve ANFIS model. ",

keywords = "ANFIS, Coronary heart disease, Heart disease prediction",

author = "Siyue Song and Tianhua Chen and Grigoris Antoniou",

note = "Publisher Copyright: {\textcopyright} 2021 ACM. Copyright: Copyright 2021 Elsevier B.V., All rights reserved.; 5th International Conference on Innovation in Artificial Intelligence, ICIAI 2021 ; Conference date: 05-03-2021 Through 08-03-2021",

year = "2021",

month = mar,

day = "5",

doi = "10.1145/3461353.3461354",

language = "English",

isbn = "9781450388634",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery (ACM)",

pages = "32--35",

booktitle = "ICIAI 2021- 5th International Conference on Innovation in Artificial Intelligence",

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Song, S, Chen, T & Antoniou, G 2021, ANFIS Models for Heart Disease Prediction. in ICIAI 2021- 5th International Conference on Innovation in Artificial Intelligence: (ICIAI 2021). ACM International Conference Proceeding Series, vol. PartF171546, Association for Computing Machinery (ACM), New York, pp. 32-35, 5th International Conference on Innovation in Artificial Intelligence, Virtual, 5/03/21. https://doi.org/10.1145/3461353.3461354

ANFIS Models for Heart Disease Prediction. / Song, Siyue; Chen, Tianhua; Antoniou, Grigoris.

ICIAI 2021- 5th International Conference on Innovation in Artificial Intelligence: (ICIAI 2021). New York : Association for Computing Machinery (ACM), 2021. p. 32-35 (ACM International Conference Proceeding Series; Vol. PartF171546).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - ANFIS Models for Heart Disease Prediction

AU - Song, Siyue

AU - Chen, Tianhua

AU - Antoniou, Grigoris

N1 - Conference code: 5

PY - 2021/3/5

Y1 - 2021/3/5

N2 - Coronary heart disease is the one of the most common diseases and a major cause of death internationally. The early detection and prediction of such disease is thus very important for human life. Currently, the Adaptive Neural Fuzzy Inference System (ANFIS) is increasingly becoming popular in the field of prediction and diagnosis of medical disease, because ANFIS can arrive at the definite conclusion by dealing with ambiguous, imprecise and vague information in activities or processes. This paper reviews the application of ANFIS in the field of heart disease prediction, as well as some innovative combinations of ANFIS and other techniques for clinical decision support on heart disease diagnosis. Finally, we identify ideas for future work aiming to improve ANFIS model.

AB - Coronary heart disease is the one of the most common diseases and a major cause of death internationally. The early detection and prediction of such disease is thus very important for human life. Currently, the Adaptive Neural Fuzzy Inference System (ANFIS) is increasingly becoming popular in the field of prediction and diagnosis of medical disease, because ANFIS can arrive at the definite conclusion by dealing with ambiguous, imprecise and vague information in activities or processes. This paper reviews the application of ANFIS in the field of heart disease prediction, as well as some innovative combinations of ANFIS and other techniques for clinical decision support on heart disease diagnosis. Finally, we identify ideas for future work aiming to improve ANFIS model.

KW - ANFIS

KW - Coronary heart disease

KW - Heart disease prediction

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U2 - 10.1145/3461353.3461354

DO - 10.1145/3461353.3461354

M3 - Conference contribution

SN - 9781450388634

T3 - ACM International Conference Proceeding Series

SP - 32

EP - 35

BT - ICIAI 2021- 5th International Conference on Innovation in Artificial Intelligence

PB - Association for Computing Machinery (ACM)

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T2 - 5th International Conference on Innovation in Artificial Intelligence

Y2 - 5 March 2021 through 8 March 2021

ER -

ANFIS Models for Heart Disease Prediction

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