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Biomedical subjects

M Hakman

Publications and source records attributed to M Hakman.

3 recordsLinked to original sources

Prediction of myocardial infarct size from early serum myoglobin observations.

Different possibilities to predict infarct size were analysed. The basic method was the fitting of a mathematical model to serial serum myoglobin concentration values from the very early phase of infarction. Correlation was performed with infarct size estimated from the complete serum curves of 53 patients. An observation period up to and including the serum peak value (on the average 6.8 h after onset) was required in order to give a well-determined value of infarct size. A correlation coefficient of r = 0.85 (n = 38) was then obtained. The serum peak concentration value of myoglobin correlated even better (r = 0.89). The initial slope of the serum curve (obtained on the average 4.3 h after onset of symptoms) also correlated well to infarct size (r = 0.80; n = 53). In conclusion, estimation of infarct size appears to be as good with the serum peak value of myoglobin as with model-based parameters. The most useful measure for early prediction of infarct size could be the initial slope of the serum curve.

Aged

KBSIM: a system for interactive knowledge-based simulation.

The KBSIM system integrates quantitative simulation with symbolic reasoning techniques, under the control of a user interface management system, using a relational database management system for data storage and interprocess communication. The system stores and processes knowledge from three distinct knowledge domains, viz. (i) knowledge about the processes of the system under investigation, expressed in terms of a Continuous System Simulation Language (CSSL); (ii) heuristic knowledge on how to reach the goals of the simulation experiment, expressed in terms of a Rule Description Language (RDL); and (iii) knowledge about the requirements of the intended users, expressed in terms of a User Interface Description Language (UIDL). The user works in an interactive environment controlling the simulation course with use of a mouse and a large screen containing a set of 'live' charts and forms. The user is assisted by an embedded 'expert system' module continuously watching both the system's behavior and the user's action, and producing alerts, alarms, comments and advice. The system was developed on a Hewlett-Packard 9000/350 workstation under the HP-Unix and HP-Windows operating systems, using the MIMER database management system, and Fortran, Prolog/Lisp and C as implementation languages. The KBSIM system has great potentials for supporting problem solving, design of working procedures and teaching related to management of highly dynamic systems.

Artificial Intelligence

KBSIM/FLUIDTHERAPY: a system for optimized design of fluid resuscitation in trauma.

An application of the KBSIM (Knowledge-Based SIMulation) system to the improved design of fluid resuscitation is described. The system integrates knowledge from three domains, viz. the pathophysiology of traumatized patients represented in a quantitative biodynamic model, the heuristics of fluid resuscitation of such patients as represented in 'production rules', and some 'metaknowledge' reflected in the design of a multi-window user interface. This technique of combining numerical simulation with symbolic reasoning has obvious advantages during the design process and in training, by giving the user a possibility to evaluate his measures by direct feedback from the system. This feature of the system to assist in evaluation of alternative resuscitation procedures should also be useful as a means for decision support.

Artificial Intelligence