A Taxonomy for Mental Illness in Healthcare System
Sumitra Mallick1, Mrutyunjaya Panda2

1Sumitra Mallick, Department of Computer Science, KL University, Hyderabad, Telangana, India.
2Mrutyunjaya Panda, Department of Computer Science and Applications, Utkal University, Odisha, India.
Manuscript received on February 10, 2020. | Revised Manuscript received on February 22, 2020. | Manuscript published on March 10, 2020. | PP: 367-371 | Volume-9 Issue-5, March 2020. | Retrieval Number: E2206039520/2020©BEIESP | DOI: 10.35940/ijitee.E2206.039520
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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: The rise in chronic diseases becomes strain in modern healthcare systems, some such disease is the mental illness. However, a solution is required to provide high quality care for the patient that is achieved through precision medicine. The precision medicine for mental illness disease is found to be taken care of because it treats the patient health by considering the individual profiles. The modern healthcare systems are encouraged to develop precision medicine to be used in the future and accessed anywhere in the world. This paper further provides a comprehensive survey of the state of art technologies of precision medicine approach for the mental illness disease. The aim of this research is to develop a taxonomy of mental illness disease by finding their symptoms along with genomes. The survey proposes a Medicare system should be developed for precision medicine considering deep learning techniques are the methodologies to classify the mental illness diseases for better accuracy and efficiency. 
Keywords: Precision Medicine, Mental Illness, Classification, Accuracy, Efficiency.
Scope of the Article: Healthcare Informatics