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Testing the ability of ChatGPT to categorise urgent and non-urgent patient conditions : who ya gonna call?
Fildor, Dorian; Pejić Bach, Mirjana - In: Proceedings of the ENTRENOVA - ENTerprise REsearch … 9 (2023) 1, pp. 101-112
patient cases to the GPT and categorising the conditions based on urgency. In collaboration with an experienced hospital …
Persistent link: https://www.econbiz.de/10014496272
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Predicting no-show appointments in a pediatric hospital in Chile using machine learning
Dunstan, J.; Villena, F.; Hoyos, J.P.; Riquelme, V.; … - In: Health care management science : a new journal serving … 26 (2023) 2, pp. 313-329
Persistent link: https://www.econbiz.de/10014315752
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Designing AI-augmented healthcare delivery systems for physician buy-in and patient acceptance
Dai, Tinglong; Tayur, Sridhar - In: Production and operations management : the flagship … 31 (2022) 12, pp. 4443-4451
Persistent link: https://www.econbiz.de/10014265858
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Quality and accountability of Large Language Models (LLMs) in healthcare in low- and middle-income countries (LMIC) : a simulated patient study using ChatGPT
Si, Yafei; Yang, Yuji; Wang, Xi; An, Ruopeng; Zu, Jiaqi; … - 2024
Using simulated patients to mimic nine established non-communicable and infectious diseases over 27 trials, we assess …
Persistent link: https://www.econbiz.de/10015062654
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Artificial intelligence as a growth engine for health care startups : emerging business models
Garbuio, Massimo; Lin, Nidthida - In: California management review 61 (2019) 2, pp. 59-83
Persistent link: https://www.econbiz.de/10012175426
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Labor shortage solution : redefining hospitality through digitization
Morosan, Cristian; Bowen, John T. - In: International journal of contemporary hospitality management 34 (2022) 12, pp. 4674-4685
Persistent link: https://www.econbiz.de/10013455349
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How do machine learning algorithms perform in predicting hospital choices? : evidence from changing environments
Raval, Devesh; Rosenbaum, Ted; Wilson, Nathan E. - In: Journal of health economics 78 (2021), pp. 1-27
Persistent link: https://www.econbiz.de/10013256262
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Reducing hospital readmission risk using predictive analytics
Mann, Arti; Cleveland, Ben; Bumblauskas, Dan; Kaparthi, … - In: INFORMS journal on applied analytics 54 (2024) 4, pp. 380-388
Persistent link: https://www.econbiz.de/10014634130
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A multi-appointment patient scheduling system with machine learning and optimization
Han, Ying; Johnson, Marina Evrim; Shan, Xiaojun; … - In: Decision analytics journal 10 (2024), pp. 1-16
Appointment scheduling is critical to increasing resource utilization and operational performance in various industry domains, especially healthcare. Costs to care for several serious diseases are projected to grow due to the aging population and rising drug prices. Thus, there is an urgent need...
Persistent link: https://www.econbiz.de/10014541622
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Predictive analytics of readmission risk in hospitals for an intelligent decision support system
Eigner, Isabella - 2021
Persistent link: https://www.econbiz.de/10014021945