Implementation of Artificial Fish Swarm Optimization for Cardiovascular Heart Disease
A.M. Barani1, R.Latha2, R.Manikandan3

1A. M. Barani, Department of Computer Applications, St. Peters Institute of Higher Education & Research, Chennai (Tamil Nadu), India.
2Dr. R. Latha, Department of Computer Applications, St. Peters Institute of Higher Education & Research, Chennai (Tamil Nadu), India.
3Dr. R. Manikandan, Department of Computer Science, The Quaide Milleth College for Men, Chennai (Tamil Nadu), India.
Manuscript received on 19 January 2020 | Revised Manuscript received on 02 February 2020 | Manuscript Published on 05 February 2020 | PP: 134-136 | Volume-8 Issue-4S5 December 2019 | Retrieval Number: D10041284S519/2019©BEIESP | DOI: 10.35940/ijrte.D1004.1284S519
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Today we are living in the digital world, with a systematic life, which may leads to many new diseases due to artificial production on agriculture, mental stress, economic and social stress too. Due to machine world, patients hearts diseases can be predict by various heart diseases detection model. There are various techniques, models and tools are predicted to find the real status of heart diseases which may have advantages and disadvantages too. This paper will try to improve the performance of the new proposed techniques which is used to determine the drawback from the existing system and overcome the drawback. The proposed techniques is used to preprocess the information and moved to the next process of selection to determine accuracy, sensitivity, specificity, precision, recall and F-measure from the dataset retrieved from three major metropolitan cities likes Chennai, Bangalore and Delhi. These proposed techniques provide the more efficient and effective with the existing system with 90% to 95%.
Keywords: Artificial Production, Agriculture, Mental Stress, Economic, Social Stress, Patients Hearts Diseases.
Scope of the Article: Artificial Intelligence and Machine Learning