{VIE-PNN: An Expert System for Parenteral Nutrition of Neonates}

Conference Paper
The planning of an adequate nutritional support for meeting the metabolic requirements of sick neonates is a tedious time consuming calculation, needs practical expert knowledge and involves the risk of introducing possibly fatal errors. We therefore developed the interactive support system VIE–PNN for calculating the composition of parenteral nutrition solutions (PNS) for neonates at intensive care units. The aims were to avoid errors within certain limits, to save time, and to keep data for further statistical analysis. We combined textbook rules of nutrition planning with the knowledge of experienced physicians. The dynamic and static knowledge is represented in frame structure and backward chaining rules. The daily requirements are determined in units per kilogram body weight and have to be adjusted according to the patient's age, its body weight, and its clinical conditions (e.g. specific diseases, past and present–day blood analysis). The system uses default values and strategies of estimation in the absence of real values. The physician has the possibility to accept or to adjust proposed values on the screen. VIE–PNN offers the possibility to adjust compositions of the PNS to the total fluid intake, which is often difficult when total fluid allowance is restricted. This task is time consuming if done systematically by hand. Finally, the PNS may be reduced according to the proportion of oral feedings. The final output is a PNS schedule form, which can directly be used in the case history of neonates. A knowledge acquisition module supports the input of new bypasses and new oral feeding products. A technical, empirical and subjective evaluation of the system was performed. It proved VIE–PNN's soundness, its ability to provide a standard for the composition of parenteral nutrition, and its clinical applicability. AI topic: Configuration and Planning, Decision Support Domain area: Medicine, Neonates, Intensive Care, Parenteral Nutrition
Year of Publication
Conference Name
Proceedings of the Ninth Conference on Artificial Intelligence for Applications (CAIA-93)
IEEE Computer Society Press