Anything related to a variety of fields from statistics, data mining, machine learning or related domains. Critical issues in medical diagnosis that often go ignored or cannot be handled due to some lack in the current technology.
mass disasters... when you have 1000 wounded persons, and number of medics is limited, whom you save first? I know it seems inhumane, but:
1. is the category which may wait (and be still saved later)
2. is the category, which may not be saved (wasting of limited resources)
3. group which requires immediate attention (or it is too late).
Here you need statistically tested and simple criteria (if possible - not based on equipment), how to sort patients.
Sounds quite interesting. This problem might involve several domains. I think it might be a good start to have the vital signs of all the wounded people which might be a key parameter in this kind of a decision making scenario.
Still, I would be interested to know what strategy to look for resource management considering the fact that no two individuals have the same level of injury.
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