Case-based reasoning in postoperative pain treatment

Abstract: Even today, with modern medicine and technology, post-operative pain still exists as anmajor issue in modern treatment. A lot of research efforts have been made, in order toimprove pain outcome for patients that has undergone surgery[18][15].Even though physician's and doctors are well educated, the success rate is aboutapproximately 70 %, still there are patients that experience severe pain, after they haveundergone surgery. There could be several reasons to this, for example, lack of methods orsupport should be amongst other things, factors to consider[18].The problem has been to initiate a case-library and eventually create a tool, that could aidphycisians or doctors in their decision making, which hopefully would help in improvingpain outcome. The chosen method to do this, is a modified version of the CBR-algorithm,which is an artificial intelligence algorithm. The CBR-algorithm makes use of features,solution and outcome, and is implemented with a simple prototype, as a similarity function.The are several reasons for why this method was chosen, but using this method makes itpossible to easily create a web-based tool, so it can easily be accessed from anywhere, butstill be effective and work as a support tool.The algorithm works as a self learning mechanism, and is easy to implement, and theinterface has been constructed, allowing the phycisian or doctor to retrieve informationabout patients and run CBR. The desired results are as expected, it's possible to run theCBR, retrieve and compare cases, and get suggestion of solution or action that should beperformed.The conclusion that can be made, is that, although this is a very basic working medicalapplication, still an overall improvement is needed in order to be used as a medicalapplication. It's anyhow a start. For more details and information, check the appendicesplease.