Solving the problem of incomplete data in medical diagnosis via interval modeling

Wójtowicz, Andrzej; Żywica, Patryk; Stachowiak, Anna; Dyczkowski, Krzysztof

doi:10.1016/j.asoc.2016.05.029

Cited by 40 publications

(10 citation statements)

References 14 publications

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“…All scripts, documentation and non-sensitive data are available in [56]. As previous studies [57], [58] the repository can be downloaded under an LGPL V3 license.…”

Section: Technical Issuesmentioning

confidence: 99%

Finding the Largest Volume Parallelepipedon of Arbitrary Orientation in a Solid

et al. 2021

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3D Computer Vision algorithms are a subject of research and application for several industrial processes. The Volume of Interest (VOI) usually refer to sub-objects with basic shapes for computing these algorithms. However, in many cases the objects are available as irregular shapes with many vertices, and in order to apply algorithms effectively, it is essential to compute the largest volume parallelepipedon contained in 3D objects. There are no other approximation algorithms for finding the largest volume parallelepipedon of arbitrary orientation inscribed in a closed 3D contour with a computational cost better than the algorithm proposed in this paper, been O(n 3 ).INDEX TERMS Parallelogram, parallelepipedon, polyhedron, volume of interest (VOI).

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“…All scripts, documentation and non-sensitive data are available in [56]. As previous studies [57], [58] the repository can be downloaded under an LGPL V3 license.…”

Section: Technical Issuesmentioning

confidence: 99%

Finding the Largest Volume Parallelepipedon of Arbitrary Orientation in a Solid

et al. 2021

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“…and none is capable to find an interaction between criteria [51]. However, this fact does not limit their usability in many complex areas of application [62,87].…”

Section: Development Of An Aggregation Function 331 Assumptionsmentioning

confidence: 99%

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2021

EiN

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“…al. [15] introduced an approach to listing the interval diagnoses for a given level of missing data. Their approach uses aggregation and thresholding to evaluate and optimize the performance of reference diagnoses.…”

confidence: 99%

A New Hybrid Genetic and Information Gain Algorithm for Imputing Missing Values in Cancer Genes Datasets

Elzeki¹,

Alrahmawy²,

Elmougy³

2019

IJISA

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A DNA microarray can represent thousands of genes for studying tumor and genetic diseases in humans. Datasets of DNA microarray normally have missing values, which requires an undeniably crucial process for handling missing values. This paper presents a new algorithm, named EMII, for imputing missing values in medical datasets. EMII algorithm evolutionarily combines Information Gain (IG) and Genetic Algorithm (GA) to mutually generate imputable values. EMII algorithm is column-oriented not instance oriented than other implementation of GA which increases column correlation to the class in the same dataset. EMII algorithm is evaluated for imputing the generated missing values in four cancer gene expression standard medical datasets (Colon, Leukemia, Lung cancer-Michigan, and Prostate) via comparing the truth original complete datasets against the imputed datasets. The analysis of the experimental results reveals that the imputed values generated by EMII were almost the same as the original values besides having the same impact on the applied classifiers due to accuracy as similar as the original complete datasets. EMII has a running time of θ(n2), where n is the total number of columns.

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Solving the problem of incomplete data in medical diagnosis via interval modeling

Cited by 40 publications

References 14 publications

Finding the Largest Volume Parallelepipedon of Arbitrary Orientation in a Solid

Finding the Largest Volume Parallelepipedon of Arbitrary Orientation in a Solid

Untitled

A New Hybrid Genetic and Information Gain Algorithm for Imputing Missing Values in Cancer Genes Datasets

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