Abstract :
Kuhn, in 1970, proposed that a scientific revolution is inaugurated every time an existing paradigm ceases to function in the exploration of an aspect of nature and, thus, it is replaced by another one. Arnold M. Katz, in 1988, said that rather each new paradigm adds and complements the evolution of knowledge, but does not invalidate its predecessors. Katz illustrates his concept by analyzing three mechanisms that regulate cardiac work. i.e., by changing end-diastolic fiber length (Starling´s law), by biochemical intramyocardial cell changes (excitation-contraction coupling and contractility), and by altered gene expression (as described in molecular biology). They are not mutually exclusive and tend to complement each other. Traditional medicine can be regarded as a paradigm-that is, a wide model-after the patterns imposed, say, by biology, anatomy, physiology, biochemistry, pathology, pharmacology, and considerable empirical knowledge. Besides, if quantification is a measure the degree advancement of a scientific discipline, one may state that the main objective of bioengineering to quantify the biomedical sciences, starting with a precise definition of variables and parameters, continuing with a search for principles of transduction, a search for mathematical relationships and laws, until the predictive stage is reached, as the case is with disciplines such as astronomy and physics. Thus, biomedical engineering may be taken as a paradigmatic shift that expands and complements, without negating, the traditional medical paradigm
Keywords :
biomedical engineering; Starling´s law; altered gene expression; anatomy; biochemical intramyocardial cell changes; biochemistry; biology; biomedical engineering paradigm; cardiac work regulation; contractility; empirical knowledge; end-diastolic fiber length; excitation-contraction coupling; knowledge evolution; mathematical relationships; molecular biology; pathology; pharmacology; physiology; scientific discipline advancement; traditional medical paradigm; traditional medicine; Anatomy; Biochemical analysis; Biochemistry; Biological system modeling; Biomedical engineering; Cells (biology); Computational biology; Evolution (biology); Gene expression; Physiology;