Please use this identifier to cite or link to this item: http://dspace.aiub.edu:8080/jspui/handle/123456789/83
Title: Predicting the Demand of Prescribed Medicines in Bangladesh using Artificial Intelligent (AI) based Long Short-Term Memory (LSTM) Model
Authors: Hafiz, Muhtasim
Sazzad, Md Sabbir Ibne
Hasan, Khalid Ibne
Hasnat, Jamil
Mishu, Mahbub C.
Keywords: Computing Methodology
Machine Learning
Neural Networks
Issue Date: 10-Jan-2020
Publisher: Association for Computing Machinery
Citation: Muhtasim Hafiz, Md Sabir Ibna Sazzad, Khalid Ibne Hasan, Jamil Hasnat, and Mahbub C. Mishu. 2020. Predicting the Demand of Prescribed Medicines in Bangladesh using Artificial Intelligent (AI) based Long Short-Term Memory (LSTM) Model. In Proceedings of the International Conference on Computing Advancements (ICCA 2020). Association for Computing Machinery, New York, NY, USA, Article 2, 1–5. DOI:https://doi.org/10.1145/3377049.3377056
Series/Report no.: ICCA 2020: Proceedings of the International Conference on Computing Advancements;
Abstract: Health services are one of the necessities for a human being. Good quality and timely health services are essential for proper health conditions of human requirement. Distribution of health care facilities and services are imperative in any nation thus anticipating demand and taking pre-emptive decision to adjust the supply for the future is essential. A responsive and synchronised flow of the products is necessary. The aim of this paper is to present the forecasting model and predicted medicine demand in all district of Bangladesh.
URI: http://dspace.aiub.edu:8080/jspui/handle/123456789/83
ISBN: 978-1-4503-7778-2
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