Biomedical subjects

A V Roudsari

Publications and source records attributed to A V Roudsari.

4 recordsLinked to original sources

PubMed1994

Time series analysis and control of blood glucose levels in diabetic patients.

This paper describes features of a computer-based decision support system which is being developed to assist in the management of insulin-dependent diabetic patients. The clinical context is the provision of advice on the adjustment of the basic insulin regimen such as occurs at regular visits to the clinician. The integrated system combines data processing and interpretation, generation of qualitative advice and testing the implications of that advice using a glucose/insulin dynamic simulator. The two major features described in this paper are time series analysis of blood glucose data, and their interpretation in relation to the provision of advice for controlling the patient's blood glucose level. It is demonstrated that two approaches may be adopted in such time series analysis: an intuitive approach, manipulating symbolic representations of the data, and formal time series methods which decompose the series into clinically related components.

Blood Glucose↗

PubMed1994

Methodological issues in validating decision-support systems for insulin dosage adjustment.

Safety and reliability of advice from new computer systems should be confirmed before embarking on prospective hospital trials. This process of preliminary testing is termed 'validation'. Though it forms a fundamental stage in system development, few standards exist for choosing and implementing tests. In the present paper, a validation methodology is developed in the domain of diabetes and intended for general use in chronic health management. It is based on a peer review protocol and incorporates empirical measures indicating: applicability of results to the real environment; variation among doctors; comparisons between doctors' and computer advice; and relative merits of different computer algorithms.

Algorithms↗

PubMedDate not supplied

An integrated approach for the computer-assisted treatment of diabetic patients on insulin.

A prototype computer system has been developed to provide advice on the day-to-day adjustment of carbohydrate intake and insulin regimen in the insulin-dependent diabetic patient. The system also produces a 24-h simulation of the patient's blood glucose profile based on these adjustments. Advice is generated by a qualitative knowledge-based system which suggests what the next step in improving glycaemic control might be for a given patient, e.g. 'decrease morning short-acting insulin by 2 units'. The quantitative simulator module contains two different mathematical models. The first is a non-linear model in differential equation form which consists of a one-compartment glucose model linked to a model with free and bound insulin compartments. This physiological model is solved by a general-purpose simulation engine. The second is a linear systems model which uses a transfer function to describe the insulin input/blood glucose response relationship for individual diabetic patients. Results of a preliminary medical validation are presented.

Blood Glucose↗

PubMedDate not supplied

Validation of a metabolic prototype to assist in the treatment of insulin-dependent diabetes mellitus.

This paper describes the principles and prototyping of a computer system to assist in the treatment of patients with insulin-dependent (type 1) diabetes mellitus. The system adopts a mixed approach involving rule-based qualitative algebra and a dynamic mathematical model to define the relationships between insulin dosage, diet and glycaemic response. The rule-based system (KBS), implemented in PROLOG, can be used to generate qualitative therapeutic advice. These suggestions are quantified and rank-ordered by the use of a mathematical model of glucose-insulin interaction in type 1 diabetes mellitus, with parameters adjusted for individual patients. In this paper an overview of the integrated prototype, linking the KBS and model, is provided and a case study used to demonstrate the principles of the system in operation. The results of verification and validation work performed on the KBS are described.

Blood Glucose↗