Literature DB >> 8646833

Clinical evaluation of the DIABETES expert system for decision support by multiple regimen insulin dose adjustment.

B V Ambrosiadou1, D G Goulis, C Pappas.   

Abstract

A performance evaluation of the DIABETES rule-based expert system prototype for clinical decision making is presented. The system facilitates multiple insulin regimen and dose adjustment of insulin dependent Type I or II diabetic patients. The study was performed on 600 subjects from two diabetological centres and three diabetological offices of Greek hospitals. The responses of the attendant medical doctors were compared with those of the DIABETES system, with the aid of a specifically devised valuation range (0-5 degrees, 0 indicating full agreement and 5 full disagreement). The capabilities and the weakness of the system in terms of its practicality for decision support in assisting therapy of diabetes mellitus by blood glucose monitoring and subsequent insulin dose adjustment are discussed. The potential benefits of decision support systems for diabetic patient management are seen to be the cost saving they provide in terms of man-hours of verbal instruction by medical experts, the support in terms of objective and consistent decision making, as well as the recording of medical knowledge in the ill-defined field of insulin administration, thus aiding the education and training of medical personnel.

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Year:  1996        PMID: 8646833     DOI: 10.1016/0169-2607(95)01711-9

Source DB:  PubMed          Journal:  Comput Methods Programs Biomed        ISSN: 0169-2607            Impact factor:   5.428


  2 in total

1.  A neural network approach in diabetes management by insulin administration.

Authors:  G Gogou; N Maglaveras; B V Ambrosiadou; D Goulis; C Pappas
Journal:  J Med Syst       Date:  2001-04       Impact factor: 4.460

2.  Implementation of expert systems to support the functional evaluation of stand-to-sit activity.

Authors:  Maíra Junkes-Cunha; Glauco Cardozo; Christine F Boos; Fernando de Azevedo
Journal:  Biomed Eng Online       Date:  2014-07-21       Impact factor: 2.819

  2 in total

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