A neural network approach in diabetes management by insulin administration.

Diabetes management by insulin administration is based on medical experts' experience, intuition, and expertise. As there is very little information in medical literature concerning practical aspects of this issue, medical experts adopt their own rules for insulin regimen specification and dose adjustment. This paper investigates the application of a neural network approach for the development of a prototype system for knowledge classification in this domain.

The DELPHI method as a consensus and knowledge acquisition tool for the evaluation of the DIABETES system for insulin administration.

DIABETES is a decision-support system in the field of insulin administration. System performance evaluation is particularly difficult because of the absence of a uniform decision-making model followed by the specialists. The DELPHI method has been selected since it is appropriate for those domains where there is divergence among experts' opinions.

DIABETOR computer aided tutoring in diabetes management.

Computer Aided Instruction (CAI) and Computer Aided Learning (CAL) Systems, are software systems that can tutor people in a given domain. Medicine is a field that is particularly amenable to computer aided instruction because one is allowed to experiment with a large number of hypothetical simulated patient/disease cases, without the ill consequences of the wrong decision in real life. This paper presents an Intelligent Tutoring system for the Management of the diabetes disease, and specifically for instruction in insulin administration.

RHINE-AM. An inter-regional health information network for Europe.

RHINE is an inter-regional network in Europe having as an aim, the promotion of know-how transfer in the area of Information Technology methods and tools in the regions involved. The RHINE network's significance will be demonstrated in the health sector. Within the main scope of the project, the aims and objectives of RHINE and the participating partners encompass the extension of the nucleus network and the furtherance of Information Technology research.

Decision support for insulin regime prescription based on a neural-network approach.

Insulin regime prescription is performed by medical personnel based on a number of patient related factors such as age, activity, type of current medication, desirable control, whether the patient belongs to a special category, for example whether he has fever or has undergone surgery, etc. No general rules apply so that each expert adopts his/her own rules for insulin regime specification based on his/her experience, intuition and expertise. This is why there is very little in medical literature concerning this issue.