礼节 发表于 2025-3-23 12:30:14
Peter T. Vanberkel,Benjamin Wedge,Alix J. E. Carter,Ilze Ziedins喃喃诉苦 发表于 2025-3-23 15:31:34
Clio Dosi,Manuel Iori,Arthur Kramer,Matteo Vignoli设施 发表于 2025-3-23 18:20:53
Karen Moons,Geert Waeyenbergh,Paul Timmermans,Dirk De Ridder,Liliane Pintelon围裙 发表于 2025-3-23 23:03:16
http://reply.papertrans.cn/43/4247/424644/424644_14.png约会 发表于 2025-3-24 04:14:12
Laura Musaraganyi,Simon Germain,Nadia Lahrichi,Louis-Martin RousseauCardiac-Output 发表于 2025-3-24 10:15:17
http://reply.papertrans.cn/43/4247/424644/424644_16.png能够支付 发表于 2025-3-24 11:48:57
Non-emergency Patient Transfer Scheduling and Assignment that will minimize travel costs and balance workloads and apply it to a real-world case study. This paper also proposes a framework to utilize historical patient transfer data in the scheduling process. The mathematical model provides decision support for the non-emergency patient transfer scheduling process.MUTE 发表于 2025-3-24 15:11:56
http://reply.papertrans.cn/43/4247/424644/424644_18.png无法治愈 发表于 2025-3-24 19:06:13
http://reply.papertrans.cn/43/4247/424644/424644_19.pngfetter 发表于 2025-3-25 02:36:10
A Meta Algorithm for Reinforcement Learning: Emergency Medical Service Resource Prioritization Problon to approximate values of the upstream subspace. Using temporal difference (TD) learning as an example RL algorithm, we show that SPartAN is able to reliably derive a high-quality policy solution, thereby opening opportunities to solve many practical MDP models in healthcare system problems.