1987
DOI: 10.1007/978-3-642-95549-5_4
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Matching Patients: An Approach for Decision Support in Liver Transplantation

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Cited by 2 publications
(1 citation statement)
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“…In contrast to machine learning, CBR does not try to induce rules or models from data: it makes inferences from historical cases directly by comparing them to the current patient [88]. An early example in the field of liver transplantation was presented at AIME 1987 [89]. The CBR community has always been relatively small, but papers on CBR have been presented at many AIME conferences [90][91][92][93].…”
Section: Case-based Reasoningmentioning
confidence: 96%
“…In contrast to machine learning, CBR does not try to induce rules or models from data: it makes inferences from historical cases directly by comparing them to the current patient [88]. An early example in the field of liver transplantation was presented at AIME 1987 [89]. The CBR community has always been relatively small, but papers on CBR have been presented at many AIME conferences [90][91][92][93].…”
Section: Case-based Reasoningmentioning
confidence: 96%