Randomized controlled trials versus rough set analysis: two competing approaches for evaluating clinical data

Abstract

The present paper deals with the problem of evaluating empirical evidence for therapeutic decisions in medicine. The article discusses the views of Nancy Cartwright and John Worrall on the function that randomization plays in ascertaining causal relations with reference to the therapies applied. The main purpose of the paper is to present a general idea of alternative method of evaluating empirical evidence. The method builds on data analysis that makes use of rough set theory. The first attempts to apply the method show that it is an interesting alternative to randomized controlled trials.

Semantic, Logical, and Ethical Considerations of Patients’ Decisions in the Resolution of Moral Dilemmas

“…These may include non-standard set theories, e.g. the fuzzy set theory or the rough set theory, which provide the basis for generating decision-making algorithms (Pawlak, 2001;Rzepiński, 2014). However, the process of making decisions by patients is far less acknowledged in analyses both in the field of decision theory and philosophy.…”

“…This case is a representative example of a bioethical disagreement where a moral dilemma arises because different moral orientations are accepted by different groups of people. As regards the accepted belief systems, supporters of the pro-life moral orientation (Ślipko et al, 2010) acknowledge vastly different kinds of obligations than supporters of the pro-choice orientation (Hołówka, 2001;Różyńska, 2008;Singer, 2007;Środa, 2009). The problem lies in the fact that within these opposing orientations, the term 'abortion' is assigned entirely different meanings.…”