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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 |
Appears in Collections: | Publications: Conference |
Files in This Item:
File | Description | Size | Format | |
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Draft_DSpace_Publication_Info_Upload_MahbubConf1.pdf | conference paper | 164.82 kB | Adobe PDF | View/Open |
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