Assessing the health of patients from their trend variability of vital signs with an artificial neuromolecular system

Vital signs provide critical information about the health of a patient. There are four vital signs commonly used by healthcare professionals to evaluate a patient´s health. These are body temperature, pulse rate, respiration rate (rate of breathing), and blood pressure. This paper describes the application of an artificial neuromolecular system (ANM system), a self-organizing learning system, to evaluate the health of patients in respiration intensive care unit (RICU) from their vital signs. Experimental results show that the ANM system achieves a satisfactory result in accessing and predicting the health of patients, based on their vital signs.