Neural Computation based General Disease Prediction Model
S. Prince Mary1, B. Bharathi2, Vigneshwari. S3, Sathyabama R4
1S. Prince Mary, Department of Computer Science Engineering, Sathyabama Institute of Science and technology, Chennai- (Tamil Nadu), India.
2B. Bharathi, Department of Computer Science Engineering, Sathyabama Institute of Science and technology, Chennai- (Tamil Nadu), India.
3S. Vigneshwari, Department of Computer Science Engineering, Sathyabama Institute of Science and technology, Chennai- (Tamil Nadu), India.
4R. Sathyabama, Department of Computer Science Engineering, Sathyabama Institute of Science and technology, Chennai- (Tamil Nadu), India.
Manuscript received on 03 March 2019 | Revised Manuscript received on 07 March 2019 | Manuscript published on 30 July 2019 | PP: 5646-5649 | Volume-8 Issue-2, July 2019 | Retrieval Number: B2329078219/19©BEIESP | DOI: 10.35940/ijrte.B2329.078219
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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: To predict the patient disease using soft computing technique is the primary motto of the disease prediction system. Currently, researchers are trying to develop a disease prediction system using pattern mining technique. Here, a technique for disease prediction system using genetic algorithm and artificial neural network is proposed. The genetic algorithm is used for mining the most occurrences of disease sequences rules. To form the disease prediction system, the best rule which is obtained by means of genetic algorithm is used. Artificial neural network is trained to predict the disease. Accuracy of disease prediction is compared with other prediction techniques.
Keywords: About Four Key Words or Phrases in Alphabetical Order, Separated by Commas.
Scope of the Article: Computational Techniques in Civil Engineering