{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,12,24]],"date-time":"2024-12-24T05:07:08Z","timestamp":1735016828837,"version":"3.32.0"},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643685694","type":"electronic"}],"license":[{"start":{"date-parts":[[2024,12,20]],"date-time":"2024-12-20T00:00:00Z","timestamp":1734652800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024,12,20]]},"abstract":"<jats:p>Pharmaceutical inventory management plays a critical role in hospital operations, directly impacting both financial efficiency and patient care. Reliable forecasting of drug demand is essential for optimizing inventory management and minimizing costs. This study presents a preliminary step toward developing a comprehensive solution by leveraging Long Short-Term Memory (LSTM) networks for time series forecasting of drug demand across three types of datasets: non-stationary, intermittent, and multi-seasonal. In addition to the baseline LSTM predictions, five post-prediction strategies are introduced to enhance the accuracy of forecasts, including directional (DiL) and undirectional (UDiL) double prediction methods, as well as self-adaptation techniques such as Simple Residual Adjustment (SRA), Recursive Residual Model (RRM), and Time Adaptive Demand Forecasting Adjustment (TADFA). The results indicate significant improvements in prediction quality, particularly when employing DiL and TADFA. Furthermore, the predicted values were used to simulate the inventory management costs under a model where both overprediction and underprediction are penalized equally. This work highlights the importance of accurate forecasting and demonstrates the potential for AI-driven solutions to improve pharmaceutical inventory management in hospitals.<\/jats:p>","DOI":"10.3233\/faia241450","type":"book-chapter","created":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:49:10Z","timestamp":1734947350000},"source":"Crossref","is-referenced-by-count":0,"title":["LSTM Drug Demand Forecasting with Adjustment Strategies as a Preliminary Step Toward Optimizing Hospital Drug Inventory Management"],"prefix":"10.3233","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-9350-2541","authenticated-orcid":false,"given":"Janejira","family":"Laomala","sequence":"first","affiliation":[{"name":"Department of Interdisciplinary Science and Internationalization, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0009-0008-4336-8901","authenticated-orcid":false,"given":"Papon","family":"Tantiwanichanon","sequence":"additional","affiliation":[{"name":"Department of Interdisciplinary Science and Internationalization, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0009-0004-1673-8701","authenticated-orcid":false,"given":"Natchanon","family":"Jaruteekampron","sequence":"additional","affiliation":[{"name":"Department of Interdisciplinary Science and Internationalization, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-9682-559X","authenticated-orcid":false,"given":"Sayan","family":"Kaennakham","sequence":"additional","affiliation":[{"name":"School of Mathematics and Geoinformatics, Institute of Science, Suranaree University of Technology, Nakhon Ratchasima, 30000, Thailand"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Fuzzy Systems and Data Mining X"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA241450","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,12,23]],"date-time":"2024-12-23T09:49:10Z","timestamp":1734947350000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA241450"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,12,20]]},"ISBN":["9781643685694"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia241450","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2024,12,20]]}}}