Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services
Fuente:
arXiv
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| Auteurs principaux: | , , , , , , , |
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| Format: | Preprint |
| Publié: |
2024
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| _version_ | 1866916357373689856 |
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| author | del Río, Ana Fernández Leong, Michael Brennan Saraiva, Paulo Nazarov, Ivan Rastogi, Aditya Hassan, Moiz Tang, Dexian Periáñez, África |
| author_facet | del Río, Ana Fernández Leong, Michael Brennan Saraiva, Paulo Nazarov, Ivan Rastogi, Aditya Hassan, Moiz Tang, Dexian Periáñez, África |
| contents | Pharmacies are critical in healthcare systems, particularly in low- and middle-income countries. Procuring pharmacists with the right behavioral interventions or nudges can enhance their skills, public health awareness, and pharmacy inventory management, ensuring access to essential medicines that ultimately benefit their patients. We introduce a reinforcement learning operational system to deliver personalized behavioral interventions through mobile health applications. We illustrate its potential by discussing a series of initial experiments run with SwipeRx, an all-in-one app for pharmacists, including B2B e-commerce, in Indonesia. The proposed method has broader applications extending beyond pharmacy operations to optimize healthcare delivery. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2408_07647 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services del Río, Ana Fernández Leong, Michael Brennan Saraiva, Paulo Nazarov, Ivan Rastogi, Aditya Hassan, Moiz Tang, Dexian Periáñez, África Machine Learning Artificial Intelligence Computers and Society Data Analysis, Statistics and Probability Pharmacies are critical in healthcare systems, particularly in low- and middle-income countries. Procuring pharmacists with the right behavioral interventions or nudges can enhance their skills, public health awareness, and pharmacy inventory management, ensuring access to essential medicines that ultimately benefit their patients. We introduce a reinforcement learning operational system to deliver personalized behavioral interventions through mobile health applications. We illustrate its potential by discussing a series of initial experiments run with SwipeRx, an all-in-one app for pharmacists, including B2B e-commerce, in Indonesia. The proposed method has broader applications extending beyond pharmacy operations to optimize healthcare delivery. |
| title | Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services |
| topic | Machine Learning Artificial Intelligence Computers and Society Data Analysis, Statistics and Probability |
| url | https://arxiv.org/abs/2408.07647 |