A cognitive model for forecasting progress of multiple disorders with time relationship

Many diseases cause other diseases with strength of influences and time intervals. Prognostic and therapeutic assessments are the important part of clinical medicine as well as diagnostic assessments. In cases where a patient already has manufestations of multiple disorders (complications), progress forecasting and therapy decision by physicians without support tools are very dificult: physicians often say that "Once complications set in, the patient may die". Treating complications are difficult tasks for physicians, because they have to consider all of the complexities, possibilities and interactions between the diseases. The prediction of multiple disorders has many bundles that arise from such time-dependent interrelationships between diseases and nonlinear progress. This paper proposes a model based on time-dependent influences, which appropriately describes the progress of mulitple disorders, and gives some modificaitons for applying this model to medical domains: time-dependent influence matrix manifestation vector, therapy efficacy matrix, S-shaped curve approximation, definitions of which are provided. This research proposes an algorithm for forecasting the state of each disease on the time horizon and for evaluation of therapy alternatives with not toy example, but real patient history of multiple disorders.disorders.