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The MIMIC dataset by MIT records medical data and decisions made in the hospital: https://mimic.mit.edu/ This could be a time-series problem where a patient's status and then the action taken at each individual time step is taken into account, with the outcomes being their eventual condition and some sort of cost metric. There is the additional concern that records may be too unique to format into nice, tabular data for something like NeuroAI. |
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Me and Olivier have made an adaptation for of TerraLingua to simulate the Ebola pandemic. WHO published recently a new set of recommendations for fighting against Ebola: https://www.who.int/news/item/24-08-2026-second-meeting-of-the-ihr-emergency-committee-on-the-epidemic-of-ebola-bundibugyo-virus-disease-in-the-democratic-republic-of-the-congo-temporary-recommendations The way the virus spreads and kills people has been modeled following the information found here: https://www.who.int/news-room/fact-sheets/detail/ebola-disease The code is here: https://github.com/GPaolo/terralingua-pandemics And here there is a tool that you can install in TL to help you setup the run parameters and launch the simulation: https://github.com/GPaolo/terralingua_launcher (they are both in active development, so things will change and improve with time). |
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