Application of Learning Approaches in Healthcare
Pooja M R
Pooja M R, Department of Computer Science & Engineering, Vidyavardhaka College of Engineering, Mysur (Karnataka), India.
Manuscript received on 12 April 2021 | Revised Manuscript received on 19 April 2021 | Manuscript Accepted on 15 June 2021 | Manuscript published on 30 June 2021 | PP: 1-2 | Volume-1 Issue-3, June 2021 | Retrieval Number: 100.1/ijamst.B3005061221 | DOI:10.54105/ijamst.B3005.061321
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© The Authors. Published by Lattice Science Publication (LSP). This is an open-access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The learning approaches in healthcare would aim at phenotyping the disease based on clinical as well as physiological characteristics as ideally disease is defined and diagnosed by a combination of clinical symptoms and physiologic abnormalities. The medicine today is advanced into new realm with the growth of applications of artificial intelligence and machine learning in healthcare. This is important as we will not be addressing the target population for a specific disease alone; rather predict the likely outcome of the related disease in an unknown population of interest with the knowledge gained. This is of utmost focus especially with rare diseases, the data for which are available in lower volumes. Further, prediction outcomes available at earlier stages are important to prepare points of care to handle disastrous outcomes resulting from the diseases.
Keywords: Preprocessing, Learning, Hybrid, Objective, AI
Scope of the Article: Medicine