ANFIS Models for Heart Disease Prediction

Siyue Song, Tianhua Chen, Grigoris Antoniou

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)


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 languageEnglish
Title of host publicationICIAI 2021- 5th International Conference on Innovation in Artificial Intelligence
Subtitle of host publication(ICIAI 2021)
Place of PublicationNew York
PublisherAssociation for Computing Machinery (ACM)
Number of pages4
ISBN (Electronic)9781450388634
ISBN (Print)9781450388634
Publication statusPublished - 5 Mar 2021
Event5th International Conference on Innovation in Artificial Intelligence - Due to take place Xiamen China but held virtually due to COVID 19, Virtual
Duration: 5 Mar 20218 Mar 2021
Conference number: 5

Publication series

NameACM International Conference Proceeding Series


Conference5th International Conference on Innovation in Artificial Intelligence
Abbreviated titleICIAI 2021
Internet address


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