Semi-automatic learning of simple diagnostic scores utilizing complexity measures
نویسندگان
چکیده
منابع مشابه
Semi-automatic learning of simple diagnostic scores utilizing complexity measures
OBJECTIVE Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semi-automatic learning methods can be used to support the domain specialists. They are usually not only interested in the accuracy of the learned knowledge: the understandability and interpretability of the learned models is of ...
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Semi-automatic data mining approaches often yield better results than plain automatic methods, due to the early integration of the user’s goals. For example in the medical domain, experts are likely to favor simpler models instead of more complex models. Then, the accuracy of discovered patterns is often not the only criterion to consider. Instead, the simplicity of the discovered knowledge is ...
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Knowledge acquisition and maintenance in medical domains with a large application domain ontology is a difficult task. To reduce knowledge elicitation costs, semi-automatic learning methods can be used to support the expert. We propose diagnostic scores as a promising approach and present a method for inductive learning of diagnostic scores. It can be be refined incrementally by applying differ...
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In classification learning experiments, test subjects are presented with objects which they must categorize. The correct categories, which are known to the experimenter, are functions of the characteristics (“dimensions”) of the objects, such as size, color, brightness, and saturation. The experiments measure the relative difficulty of learning different categorizations. One major factor which ...
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ژورنال
عنوان ژورنال: Artificial Intelligence in Medicine
سال: 2006
ISSN: 0933-3657
DOI: 10.1016/j.artmed.2005.03.003