Inductive reasoning in medicine: lessons from Carl Gustav Hempel's 'inductive-statistical' model.
The purpose of this paper is to discuss both the fundamental requirements of sound scientific explanations and predictions and common fallacies that occur in explaining and predicting medical problems. To this end, the paper presents Carl Gustav Hempel's 'covering-law' model (1948 and 1962) and reviews some of the criticism of the model. The strength of Hempel's model is that it shows that inductive arguments, when applied with the requirement of maximal specificity, can serve as explanations as well as predictions. The major weakness of the 'covering-law' model, its inability to portray causal relatedness, has been addressed by philosophers such as Wesley Salmon. While few philosophers today agree with the 'covering-law' model in its original formulation, there is widespread consensus that the law has made a central contribution to describing the fundamental requirements of sound scientific explanations. Applying this model and its revisions in the medical context may help uncover potentially undetected fallacies in reasoning when explaining and predicting medical problems.
Gandjour
Afschin
A
Institute of Health Economics and Clinical Epidemiology, University of Cologne, Cologne, Germany. afschin.gandjour@medizin.uni-koeln.de
Lauterbach
Karl Wilhelm
KW
D035843:Biomedical Research; D001943:Breast Neoplasms / Q000000981:diagnostic imaging; D015984:Causality; D019317:Evidence-Based Medicine; D005260:Female; D006302:Health Services Research; D006801:Humans; D008128:Logic; D008327:Mammography; D008962:Models, Theoretical; D010686:Philosophy, Medical; D012680:Sensitivity and Specificity; D035501:Uncertainty