Forecasting the market needs for medicines based on artificial intelligence technologies

The article is devoted to the issues of forecasting market demand for medicines using modern artificial intelligence (AI) technologies. In a dynamically changing medical landscape and increasing consumer variability, accurately and effectively forecasting demand for medical products is critical for...

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Bibliographic Details
Main Authors: Muhamediyeva, Dilnoz, Samijonov, Abdurashid, Alimbaev, Kamal, Bakhtiyorov, Shakhzodbek
Format: Conference Proceeding
Language:English
Subjects:
Artificial intelligence
Big Data
Demand
Forecasting
Fuzzy sets
Health care
Inventory management
Machine learning
Medical electronics
Pharmaceutical industry
Pharmaceuticals
Online Access:Get full text
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Summary:The article is devoted to the issues of forecasting market demand for medicines using modern artificial intelligence (AI) technologies. In a dynamically changing medical landscape and increasing consumer variability, accurately and effectively forecasting demand for medical products is critical for pharmaceutical companies and healthcare systems. The article examines methods and approaches that use AI technologies such as machine learning, big data analytics, and fuzzy sets to create accurate and predictive drug demand forecasting models. Modern approaches to the collection, storage and processing of medical data, which play a key role in the forecasting process, are analyzed. The article also provides practical examples of the successful implementation of AI technologies in the pharmaceutical industry and provides recommendations for their implementation to optimize production, logistics and drug inventory management. The article describes the importance of collaboration between pharmaceutical companies and artificial intelligence specialists, and also puts forward prospects for the further development of this field of research in the context of modern challenges and opportunities in the field of healthcare and pharmaceuticals.
ISSN:0094-243X
1551-7616
DOI:10.1063/5.0210445