Adaptive Behavioral AI: Reinforcement Learning to Enhance Pharmacy Services

Autor:	del Río, Ana Fernández, Leong, Michael Brennan, Saraiva, Paulo, Nazarov, Ivan, Rastogi, Aditya, Hassan, Moiz, Tang, Dexian, Periáñez, África
Rok vydání:	2024
Předmět:	Computer Science - Machine Learning Computer Science - Artificial Intelligence Computer Science - Computers and Society Physics - Data Analysis Statistics and Probability
Druh dokumentu:	Working Paper
Popis:	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. Comment: Presented at The First Workshop on AI Behavioral Science (AIBS'24) at KDD 2024, August 25, Barcelona, Spain
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2408.07647 Zobrazit plný text záznamu View this record from Arxiv