A patient enters the hospital with severe abdominal pains. Based on past experience, Doctor Craig believes there is a 28% chance that the patient has appendicitis and a 72% chance that the patient has nonspecific abdominal pains. Dr. Craig may operate on the patient now or wait 12 hours to gain a more accurate diagnosis. In 12 hours, Dr. Craig will surely know whether the patient has appendicitis. The problem is that in the meantime, the patient’s appendix may perforate (if he has appendicitis), thereby making the operation much more dangerous. Again based on past experience, Dr. Craig believes that if he waits 12 hours, there is a 6% chance that the patient will end up with a perforated appendix, a 22% chance the patient will end up with “normal” appendicitis, and a 72% chance that the patient will end up with nonspecific abdominal pain. From past experience, Dr. Craig assesses the probabilities shown in Table of the patient dying.
Situation
Probability That Patient Will Die
Operation on patient
.0009
with appendicitis
.0004
with nonspecific
abdominal pain
Operation on perforated
.0064
appendix
No operation on patient
0
Assume that Dr. Craig’s goal is to maximize the probability that the patient will survive. Use a decision tree to help Dr. Craig make the right decision.
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