Mining answers for causal questions in a medical example

The aim of this paper is to approach causal questions in a medical domain. Causal questions par excellence are what, how and why-questions. The `pyramid of questions' shows this. At the top, why-questions are the prototype of causal questions. Usually why-questions are related to scientific explanations. Although cover law explanation is characteristically of physical sciences, it is less common in biological or medical knowledge. In medicine, laws applied to all cases are rare. It seems that doctors express their knowledge using mechanisms instead of natural laws. In this paper we will approach causal questions with the aim of: (1) answering what-questions as identifying the cause of an effect; (2) answering how-questions as selecting an appropriate part of a mechanism that relates pairs of cause-effect (3) answering why-questions as identifying ultimate causes in the answers of how-questions. In this task, we hypothesize that why-questions are related to scientific explanations in a negative and a positive note: (i) as previously said, scientific explanations in biology are based on mechanisms instead of natural laws; (ii) scientific explanations are generally concerned with deepening, providing explanations as detailed as possible. Thus, we conjecture that answers to why-questions have to find the ultimate causes in a mechanism and link them to the prior cause summarizing the intermediate nodes in order to provide a comprehensible answer. The Mackie's INUS causality offers a theoretical support for this solution.