About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature

Yury Mikhailovich Petrenko

doi:doi:10.11648/j.ijdsa.20190501.12

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About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature

Yury Mikhailovich Petrenko

Published in International Journal of Data Science and Analysis (Volume 5, Issue 1)

Received: 19 January 2019 Accepted: 19 March 2019 Published: 10 May 2019

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Abstract

The literature presents a large number of very different ways to diagnose, predict and classify. In support of their usefulness and effectiveness, various parameters are often used, from a large number of them, which are not always necessary and sufficient, since they do not unequivocally characterize efficiency. The purpose of this work was to build a theory in which the characteristic parameters would be clearly defined, necessary and sufficient to identify and evaluate the effectiveness of the method itself and the databases to which this method was applied. On the basis of an objective analysis of all known parameters characterizing the effectiveness of various methods of diagnosing and predicting, necessary and sufficient conditions were determined for them that ensure the unambiguity of the conducted assessments of their effectiveness. Some examples have shown their effectiveness. Full unambiguity and certainty in the reflection of the effectiveness of any method of diagnosis and prediction is achieved only when all the parameters characterizing it are interconnected by one equation. The paper presents a set of such equations, from which it follows that the uniqueness of the evaluation of the effectiveness of any method is achieved only when it is reflected by a triad of characteristic basis parameters. Only such a triad of efficiency parameters, interconnected by characteristic equations obtained in theory, that is, in a deterministic way, can one achieve an unambiguous estimate of efficiency and its interpretation. It is important that the parameters characterizing the data arrays for which one or another method is tested can also act as basic parameters. On the basis of the equations obtained in the work, by means of the triad of basic parameters, all other parameters are determined, diversifying the efficiency. One of these triads includes sensitivity, specificity and accuracy, which in this combination uniquely determine efficiency. In this paper, from these positions, data of some works of recent years are analyzed.

Published in	International Journal of Data Science and Analysis (Volume 5, Issue 1)
DOI	10.11648/j.ijdsa.20190501.12
Page(s)	6-12
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2019. Published by Science Publishing Group

Keywords

Characteristic Parameters, Sensitivity, Specificity, Accuracy, Basic Equations

References

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[2]	Malishevsky M. V., Golodnev Y. V., Fedorova E. E., Belova N. V. // Method for predicting lethal outcome in nephrological patients // Patent RU 2254803C1 of December 31, 2003.
[3]	Gridasova R. A., Mikashinovich Z. A., Olempiyeva E. V., Terentyev V. P. // A method for predicting recurrent myocardial infarction // Patent RU 2424531C1 of May 14, 2010.
[4]	Barkova E. N., Kuznetsov V. V., Sivkov O. G. // A method for predicting an unfavorable course of sepsis // Patent RU 2315311 C1 of July 31, 2006.
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[6]	Mayorova M. V., Konkina E. A., Demidov V. I., Mishina I. E., Mazanko O. E., Berezin M. V., // A method for predicting the outcome of myocardial infarction in diabetic patients // Patent RU 2420228 C2 of April 2, 2009.
[7]	Dabizheva A. N., Kade A. Kh., Kolesnikova N. V., Chudilova G. A. // A method for predicting the lethal outcome of a large-focal myocardial infarction // Patent RU 2246114 C2 of February 18, 2003.
[8]	Gravning J., Kjekshus J. // The perfect biomarker in acute coronary syndrome: a challenge for diagnosis, prognosis, and treatment //European Heart journal, 2008, 29, 827-2828.
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[10]	Luvizutto G. J., Fogaroli M. Q., Theotonio R. M., Nunes H. R., Resende L. A., Bazan R.//Standartization of the face –hand test in a Brazilian multicultural population: prevalence of sensory extinction and implications for neurological diagnosis//Clinics (Sao Paulo), 2016, 71 (12), 720 -724.
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Yury Mikhailovich Petrenko. (2019). About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature. International Journal of Data Science and Analysis, 5(1), 6-12. https://doi.org/10.11648/j.ijdsa.20190501.12

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ACS Style

Yury Mikhailovich Petrenko. About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature. Int. J. Data Sci. Anal. 2019, 5(1), 6-12. doi: 10.11648/j.ijdsa.20190501.12

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AMA Style

Yury Mikhailovich Petrenko. About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature. Int J Data Sci Anal. 2019;5(1):6-12. doi: 10.11648/j.ijdsa.20190501.12

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@article{10.11648/j.ijdsa.20190501.12,
  author = {Yury Mikhailovich Petrenko},
  title = {About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature},
  journal = {International Journal of Data Science and Analysis},
  volume = {5},
  number = {1},
  pages = {6-12},
  doi = {10.11648/j.ijdsa.20190501.12},
  url = {https://doi.org/10.11648/j.ijdsa.20190501.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20190501.12},
  abstract = {The literature presents a large number of very different ways to diagnose, predict and classify. In support of their usefulness and effectiveness, various parameters are often used, from a large number of them, which are not always necessary and sufficient, since they do not unequivocally characterize efficiency. The purpose of this work was to build a theory in which the characteristic parameters would be clearly defined, necessary and sufficient to identify and evaluate the effectiveness of the method itself and the databases to which this method was applied. On the basis of an objective analysis of all known parameters characterizing the effectiveness of various methods of diagnosing and predicting, necessary and sufficient conditions were determined for them that ensure the unambiguity of the conducted assessments of their effectiveness. Some examples have shown their effectiveness. Full unambiguity and certainty in the reflection of the effectiveness of any method of diagnosis and prediction is achieved only when all the parameters characterizing it are interconnected by one equation. The paper presents a set of such equations, from which it follows that the uniqueness of the evaluation of the effectiveness of any method is achieved only when it is reflected by a triad of characteristic basis parameters. Only such a triad of efficiency parameters, interconnected by characteristic equations obtained in theory, that is, in a deterministic way, can one achieve an unambiguous estimate of efficiency and its interpretation. It is important that the parameters characterizing the data arrays for which one or another method is tested can also act as basic parameters. On the basis of the equations obtained in the work, by means of the triad of basic parameters, all other parameters are determined, diversifying the efficiency. One of these triads includes sensitivity, specificity and accuracy, which in this combination uniquely determine efficiency. In this paper, from these positions, data of some works of recent years are analyzed.},
 year = {2019}
}

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TY  - JOUR
T1  - About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature
AU  - Yury Mikhailovich Petrenko
Y1  - 2019/05/10
PY  - 2019
N1  - https://doi.org/10.11648/j.ijdsa.20190501.12
DO  - 10.11648/j.ijdsa.20190501.12
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 6
EP  - 12
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20190501.12
AB  - The literature presents a large number of very different ways to diagnose, predict and classify. In support of their usefulness and effectiveness, various parameters are often used, from a large number of them, which are not always necessary and sufficient, since they do not unequivocally characterize efficiency. The purpose of this work was to build a theory in which the characteristic parameters would be clearly defined, necessary and sufficient to identify and evaluate the effectiveness of the method itself and the databases to which this method was applied. On the basis of an objective analysis of all known parameters characterizing the effectiveness of various methods of diagnosing and predicting, necessary and sufficient conditions were determined for them that ensure the unambiguity of the conducted assessments of their effectiveness. Some examples have shown their effectiveness. Full unambiguity and certainty in the reflection of the effectiveness of any method of diagnosis and prediction is achieved only when all the parameters characterizing it are interconnected by one equation. The paper presents a set of such equations, from which it follows that the uniqueness of the evaluation of the effectiveness of any method is achieved only when it is reflected by a triad of characteristic basis parameters. Only such a triad of efficiency parameters, interconnected by characteristic equations obtained in theory, that is, in a deterministic way, can one achieve an unambiguous estimate of efficiency and its interpretation. It is important that the parameters characterizing the data arrays for which one or another method is tested can also act as basic parameters. On the basis of the equations obtained in the work, by means of the triad of basic parameters, all other parameters are determined, diversifying the efficiency. One of these triads includes sensitivity, specificity and accuracy, which in this combination uniquely determine efficiency. In this paper, from these positions, data of some works of recent years are analyzed.
VL  - 5
IS  - 1
ER  -

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Author Information

Yury Mikhailovich Petrenko

Medical and Biological Faculty, Pirogov Russian National Research Medical University, Moscow, Russian Federation

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APA Style

Yury Mikhailovich Petrenko. (2019). About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature. International Journal of Data Science and Analysis, 5(1), 6-12. https://doi.org/10.11648/j.ijdsa.20190501.12

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ACS Style

Yury Mikhailovich Petrenko. About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature. Int. J. Data Sci. Anal. 2019, 5(1), 6-12. doi: 10.11648/j.ijdsa.20190501.12

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AMA Style

Yury Mikhailovich Petrenko. About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature. Int J Data Sci Anal. 2019;5(1):6-12. doi: 10.11648/j.ijdsa.20190501.12

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@article{10.11648/j.ijdsa.20190501.12,
  author = {Yury Mikhailovich Petrenko},
  title = {About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature},
  journal = {International Journal of Data Science and Analysis},
  volume = {5},
  number = {1},
  pages = {6-12},
  doi = {10.11648/j.ijdsa.20190501.12},
  url = {https://doi.org/10.11648/j.ijdsa.20190501.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ijdsa.20190501.12},
  abstract = {The literature presents a large number of very different ways to diagnose, predict and classify. In support of their usefulness and effectiveness, various parameters are often used, from a large number of them, which are not always necessary and sufficient, since they do not unequivocally characterize efficiency. The purpose of this work was to build a theory in which the characteristic parameters would be clearly defined, necessary and sufficient to identify and evaluate the effectiveness of the method itself and the databases to which this method was applied. On the basis of an objective analysis of all known parameters characterizing the effectiveness of various methods of diagnosing and predicting, necessary and sufficient conditions were determined for them that ensure the unambiguity of the conducted assessments of their effectiveness. Some examples have shown their effectiveness. Full unambiguity and certainty in the reflection of the effectiveness of any method of diagnosis and prediction is achieved only when all the parameters characterizing it are interconnected by one equation. The paper presents a set of such equations, from which it follows that the uniqueness of the evaluation of the effectiveness of any method is achieved only when it is reflected by a triad of characteristic basis parameters. Only such a triad of efficiency parameters, interconnected by characteristic equations obtained in theory, that is, in a deterministic way, can one achieve an unambiguous estimate of efficiency and its interpretation. It is important that the parameters characterizing the data arrays for which one or another method is tested can also act as basic parameters. On the basis of the equations obtained in the work, by means of the triad of basic parameters, all other parameters are determined, diversifying the efficiency. One of these triads includes sensitivity, specificity and accuracy, which in this combination uniquely determine efficiency. In this paper, from these positions, data of some works of recent years are analyzed.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - About the Evaluation of the Effectiveness of Various Methods of Diagnosis, Prediction and Classification Presented in the Literature
AU  - Yury Mikhailovich Petrenko
Y1  - 2019/05/10
PY  - 2019
N1  - https://doi.org/10.11648/j.ijdsa.20190501.12
DO  - 10.11648/j.ijdsa.20190501.12
T2  - International Journal of Data Science and Analysis
JF  - International Journal of Data Science and Analysis
JO  - International Journal of Data Science and Analysis
SP  - 6
EP  - 12
PB  - Science Publishing Group
SN  - 2575-1891
UR  - https://doi.org/10.11648/j.ijdsa.20190501.12
AB  - The literature presents a large number of very different ways to diagnose, predict and classify. In support of their usefulness and effectiveness, various parameters are often used, from a large number of them, which are not always necessary and sufficient, since they do not unequivocally characterize efficiency. The purpose of this work was to build a theory in which the characteristic parameters would be clearly defined, necessary and sufficient to identify and evaluate the effectiveness of the method itself and the databases to which this method was applied. On the basis of an objective analysis of all known parameters characterizing the effectiveness of various methods of diagnosing and predicting, necessary and sufficient conditions were determined for them that ensure the unambiguity of the conducted assessments of their effectiveness. Some examples have shown their effectiveness. Full unambiguity and certainty in the reflection of the effectiveness of any method of diagnosis and prediction is achieved only when all the parameters characterizing it are interconnected by one equation. The paper presents a set of such equations, from which it follows that the uniqueness of the evaluation of the effectiveness of any method is achieved only when it is reflected by a triad of characteristic basis parameters. Only such a triad of efficiency parameters, interconnected by characteristic equations obtained in theory, that is, in a deterministic way, can one achieve an unambiguous estimate of efficiency and its interpretation. It is important that the parameters characterizing the data arrays for which one or another method is tested can also act as basic parameters. On the basis of the equations obtained in the work, by means of the triad of basic parameters, all other parameters are determined, diversifying the efficiency. One of these triads includes sensitivity, specificity and accuracy, which in this combination uniquely determine efficiency. In this paper, from these positions, data of some works of recent years are analyzed.
VL  - 5
IS  - 1
ER  -

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