Predictive Mechanism for Medicines Availability in Government Health Centers
Neeraja1, Pradeep Kumar J2
1Neeraja*, Associate Professor, Department of Information Technology, MLR Institute of Technology, Dundigal, Hyderabad.
2Pradeep Kumar J, Assistant Professor, Department of Information Technology, MLR Institute of Technology, Dundigal, Hyderabad.
Manuscript received on May 06, 2020. | Revised Manuscript received on May 15, 2020. | Manuscript published on June 30, 2020. | PP: 1619-1621 | Volume-9 Issue-5, June 2020. | Retrieval Number: B3011129219 /2020©BEIESP | DOI: 10.35940/ijeat.B3011.029320
Open Access | Ethics and Policies | Cite | Mendeley
© 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: During the peak time of a disease, some medicines are not available in the hospital. Now-a-days, medicines play an important role in medical science. To treat a patient there are absence of medications in government emergency clinics. Our fundamental point of our venture is to build up a Healthcare Information framework to give prescient examination on Medicines accessibility in Government clinics. In view of patient inflow for a specific affliction or ailment, authentic information and current information, framework could produce a report on what all medications ought to be accessible in the clinic. On expanding the productivity of the emergency clinic by overseeing accessibility of medicines utilizing machine learning algorithm (regression technique). This encourages government emergency clinics to follow the medicines accessibility of a specific occasional infection.
Keywords: Hive, Machine Learning, Pyhive.