Literature DB >> 10648846

A genetic algorithm approach to multi-disorder diagnosis.

S Vinterbo1, L Ohno-Machado.   

Abstract

One of the common limitations of expert systems for medical diagnosis is that they make an implicit assumption that multiple disorders do not co-occur in a single patient. The need for this simplifying assumption stems from the fact that finding minimal sets of disorders that cover all symptoms for a given patient is generally computationally intractable (NP-hard). In this paper, we explain the need for performing multi-disorder diagnosis, review previous approaches, formulate the problem using set theory notation, and propose the use of a search method based on a genetic algorithm. We test the algorithm and compare it to another approach using a simple example. The genetic algorithm performs well independently of the order of symptoms, and has the potential to perform multi-disorder diagnosis using existing or newly developed knowledge bases.

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Year:  2000        PMID: 10648846     DOI: 10.1016/s0933-3657(99)00036-6

Source DB:  PubMed          Journal:  Artif Intell Med        ISSN: 0933-3657            Impact factor:   5.326


  4 in total

1.  Generation of dynamically configured check lists for intra-operative problems using a set of covering algorithms.

Authors:  T Sawa; L Ohno-Machado
Journal:  Proc AMIA Symp       Date:  2001

2.  A technique for identifying three diagnostic findings using association analysis.

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Journal:  Med Biol Eng Comput       Date:  2006-12-15       Impact factor: 2.602

3.  Prediction of mortality in an Indian intensive care unit. Comparison between APACHE II and artificial neural networks.

Authors:  Ashish Nimgaonkar; Dilip R Karnad; S Sudarshan; Lucila Ohno-Machado; Isaac Kohane
Journal:  Intensive Care Med       Date:  2004-01-15       Impact factor: 17.440

4.  A Dedicated Genetic Algorithm for Localization of Moving Magnetic Objects.

Authors:  Roger Alimi; Eyal Weiss; Tsuriel Ram-Cohen; Nir Geron; Idan Yogev
Journal:  Sensors (Basel)       Date:  2015-09-18       Impact factor: 3.576

  4 in total

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