The functioning of the human body is characterized by the complex and highly interactive interplay of its organs and the psyche. The goal of this concerted effort is Homeostasis, the equilibrium of all physiological quantities. While the actual level at which the balance is maintained varies —within physiological bounds— from individual to individual, deviations from it are indicative of some kind of perturbation, be it of internal or of external cause. The identification of these perturbations is the goal of medical diagnosis. But this goal usually can not be achieved from the initial history, presenting complaints, and physical examination. Tests or re-examination may be needed to determine the appropriate diagnosis. The tool for directing the diagnostic process is the Differential Diagnosis. The differential diagnosis identifies possible explanations for the known findings, identifies states that have been ruled out, and provides the data needed to determine what information can be used to refine the diagnosis.
With the (differential) diagnostic means available today, it is often impossible to look inside a sick patient and determine the primary cause that led to the (series of) effects and reactions the patient complains about. More often than not, diagnosis is therefore based on indirect evidence, the presence of symptoms, and the knowledge of the medical mechanisms that relate presumed causes to observed effects. So the problems of diagnosis do not only arise from the incompleteness of this knowledge, but also and most immediately from the theoretical and practical limitations associated with the reversal of the chain of implications that lead from an initial cause to its observable effects. First of all, the body of today’s medical entities is too huge; e.g., a very large scope of initial data (more than 300 characteristics being measured mainly using numeral scales) is collected while a patient is examined in modern diagnostic centers. If each of these characteristics is measured only using the most simple name-scales (“yes-no”, “more-less”), the quantity of initial data will make which is substantially higher than the number of elemental particles in all visible Universe. Secondly, medical cause-effect relationships —the relations between diagnoses and their symptoms— are hardly ever one-to-one. Differentiation of diagnoses that share an overlapping range of symptoms is therefore inherently difficult. Thirdly, all observation is subject to error and the correction of this error, stochastic in nature, requires strong assumptions that do not hold in practice. Lastly, the required observations can often not be made on a continuous basis. Quite the contrary, because many diagnostically meaningful observations can only be obtained at rather high risk or cost, one has to make do with significantly less than desirable information. This is especially a problem for the diagnosis of dynamic disorders that evolve over an extended period of time. Although taken alone none of the problems is unique to the medical domain, taken together they add to an intricacy surpassing that of even the most sophisticated man-made systems known today. It is therefore realistic to expect that medical diagnosis will for a long time remain problematic.