The Manipulation of Medical Literature as Interference of Medical Sciences in order to Formulate New Hypotheses

In this study we present a theoretical framework that can be used to explore the possibilities of automatic hypothesis generation from medical literature. We use the model of disconnected logic developed by D.R. Swanson. The assumption is that there exist complementary but disconnected literatures from which new information can be obtained when these literatures are connected. The theoretical framework provides a set of heuristics rules which are tested with empirical data derived from a medical literature database. The field of medical and pharmaceutical sciences can be divided into many subdisciplines which are more or less related amongst each other. The resulting scientific literature of these subdisciplines has strong intra-subdisciplinary connections, but weak inter-subdisciplinary connections. This means that knowledge from the one subdiscipline is not always integrated in the scientific research of another subdiscipline. We intend to interfere in these sciences by offering a theoretical model and the computational tools that provide a way to obtain new hypotheses from existing literature, by connecting knowledge from the different subdisciplines. Recent developments in computer text analysis have made it feasible to process large amounts of texts and thus address the question of automatic literature based scientific discovery in medical and pharmaceutical research. This study combines the novel approach of actively reconstructing implicit or hidden logical inference patterns in scientific literature with recent approaches to statistical and information-theoretical analysis of (large amounts of) raw medical texts. We explore and model the development of an automatic literature-based drug discovery