Decision trees in real world medical decision making
Zorman, Milan ...
The decision tree approach is one of the most common approaches in automatic learning and decision making. It is popular for its simplicity in constructing, efficient use in decision making and for ...simple representation, which is easily understood by humans. The automatic learning of decision trees and their use usually show very good results in various "theoritical" environments. The training sets are usually large enough for learning algorithm to construct a hypothesis consistent with the underlying concept. But in real life it is often impossible to find the desired number of training objects for various reasons. The lack of possibilities to measure attribute values, high cost and complexity of such measurements, unavailability of all attributes at the same time are the typical representatives. There are different ways to deal with some of these problems. In a delicate field of medical decision making, we cannot allow ourselves to make any inaccurate decision. We have measured the values of 24 attributes before and after the 82 operations of children in age between 2 and 10 years. The aim was to find the dependencies between attribute values and a child's predisposition to acidemia - the decrease of blood's pH. Our main interest was in discovering predisposition to two forms of acidosis, the metabolic acidosis and the respirtory acidosis, which can both have serious effects on child's health. We decided to construct different decision trees from a set of training objects, which was complete (there were no missing attribute values), but on the other hand not large enough to avoid the effect of overfitting. A common approach to evaluation of a decision tree is the use of a test set. In our case we decided that instead of using a test set, we ask medical experts to take a closer look at the generated trees. They comments on one of the generated trees can be found in this paper. The comments show, that the tree, generated from available training set mainly has surprisingly good branches, but on the other hand some are very "stupid" and no medical explanation could be found. Thereafter we can conclude, that the decision tree concept and automatic learning can be successfully used in real world situations, constrained with the real world limitations, but they should be used only with the guidelines of appropriate medical experts.
It was not necessary to add the material to the shelf.
Bibliographic material was successfully added on shelf.
Adding bibliographical material on shelf was not successful.
Material is already on the shelf.
Permalink
URL:
Impact factor
Access to the JCR database is permitted only to users from Slovenia. Your current IP address is not on the list of IP addresses with access permission, and authentication with the relevant AAI accout is required.
Year
Impact factor
Edition
Category
Classification
JCR
SNIP
JCR
SNIP
JCR
SNIP
JCR
SNIP
Select the library membership card:
DRS,
in which the journal is indexed
Database name
Field
Year
Links to authors' personal bibliographies
Links to information on researchers in the SICRIS system
Subject headings in COBISS General List of Subject Headings
Select pickup location
The material from the parent unit is free. If the material is delivered to the pickup location from another unit, the library may charge you for this service.
