nach oben

Scientific and Technical Information Processing

Erschienen in:

01.12.2021

On the Reliability of Medical Diagnosis Based on Empirical Data

verfasst von: M. I. Zabezhailo, Y. Y. Trunin

Erschienen in: Scientific and Technical Information Processing | Ausgabe 5/2021

Einloggen

Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.

search-config

KI-gestützte Suche

Aus

Abstract

Some ways to apply intelligent data analysis (IDA) tools to support medical diagnostic decision-making are discussed. An original technique to identify and to delete artifacts of computer analysis data, whose performance is demonstrated based on the example of the problems of diagnosing pseudoprogression of human brain tumors, is proposed.

Vorheriger Artikel Personal Meaning and Solving Creative Tasks: Contemporary Neurocognitive Studies

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

über 102.000 Bücher
über 537 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Finance + Banking
Management + Führung
Marketing + Vertrieb
Maschinenbau + Werkstoffe
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 340 Zeitschriften

aus folgenden Fachgebieten:

Bauwesen + Immobilien
Business IT + Informatik
Finance + Banking
Management + Führung
Marketing + Vertrieb
Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

über 67.000 Bücher
über 390 Zeitschriften

aus folgenden Fachgebieten:

Automobil + Motoren
Bauwesen + Immobilien
Business IT + Informatik
Elektrotechnik + Elektronik
Energie + Nachhaltigkeit
Maschinenbau + Werkstoffe

Jetzt Wissensvorsprung sichern!

Jetzt informieren

Based on the data that are available at the moment.

“In four large hospitals in Moscow, in 21.6% of cases during life, the diagnosis turned out to be incorrect, in 20% pneumonia was not diagnosed, in 30–40% malignant neoplasms were not diagnosed…,”—the data, which are cited by V. V. Gribova with a reference to the Corresponding Member of the Russian Academy of Sciences G.B. Fedoseev (see, for example, https://itmcongress.ru/itm2020/stream/?view=nmo) in her report “What intelligent technologies for practical medicine must be” on October 16, 2020 at the Congress on Information Technologies in Medicine.

In this case, the fact of the presence of a cyst itself is a signal about the possible origin of PsP in a given patient, and the combination of all three factors gives this conclusion a priority character.

Fedoseev, G.B., Medical errors: nature, reasons, consequences and recovering, Terapiya, 2018, no. 5, pp. 109–115. https://doi.org/10.18565/therapy.2018.5.109-115

Zabezhailo, M.I. and Trunin, Yu.Yu., To the evidence of medical diagnosis: intelligent data analysis of limited size samples of describing patients empirical data, Tsifrovoe zdravookhranenye: XX Kongress Informatsionnye tekhnologii v medicine (Digital Healthcare: XX Congress Information Technologies in Medicine), 2019.

Zabezhailo, M.I. and Trunin, Yu.Yu, On the problem of medical diagnostic evidence: intelligent analysis of empirical data on patients in samples of limited size, Autom. Doc. Math. Linguist., 2019, vol. 53, no. 6, pp. 322–328. https://doi.org/10.3103/S0005105519060086CrossRef

Zabezhailo, M.I., To the complexity of characteristic function sets providing correct diagnostic solutions, 19 Vserossyiskaya Konf. Matematicheskye metody raspoznavanya obrazov (MMRO-2019) (Mathematical Methods in Pattern Recognition (MMPR-2019)), Moscow, 2019, pp. 305–306.

Zabezhailo, M., On the complexity of characteristic function sets providing correct solutions for diagnostic type tasks, Comp. Math. Math. Phys., 2021.

Zabezhailo, M., Some estimates of computational complexity when predicting the properties of new objects using characteristic functions, Autom. Doc. Math. Linguist., 2020, vol. 54, no. 6, 298–305. https://doi.org/10.3103/S0005105520060072CrossRef

Grusho, A., Zabezhailo, M., and Timonina, E., On causal representativeness of training samples of precedents in diagnostic type tasks, Inf. Primen., 2020, vol. 14, no. 1, pp. 80–86. https://doi.org/10.14357/19922264200111CrossRef

Vorontsov, K.V., Combinatoric theory of learning reliability by use cases, Doctoral (Phys.-Math.) Dissertation, Moscow: Dorodnicyn Computing Centre, 2010.

Vinogradov, D.V., Probabilistic-combinatoric formal learning method based on the grid theory, Doctoral (Phys.-Math.) Dissertation, Moscow: Federal Research Center Computer Science and Control, 2019. http:// www.frccsc.ru/diss-council/00207305/diss/list/vinogradov_dv

10.

Finn, V.K., J.S. Mill’s inductive methods in artificial intelligence systems. Part I, Sci. Tech. Inf. Process., 2011, vol. 38, no. 6, pp. 385–402. https://doi.org/10.3103/S0147688211060037CrossRef

11.

Finn, V.K., J.S. Mill’s inductive methods in artificial intelligence systems. Part II, Sci. Tech. Inf. Process., 2011, vol. 39, no. 5, pp. 241–260. https://doi.org/10.3103/S0147688212050036CrossRef

12.

Landau L.D. Fundamental problems, Teoretitcheskaya fizika XX veka (Theoretical Physics of XXth Century), Smorodinskii, Ya.A., Moscow: Inostrannaya Literatura, 1962, pp. 285–291.

13.

Abrikosov, A.A., Academician L.D. Landau, Moscow: Nauka, 1965.

14.

Zabezhailo, M.I., Some capabilities of enumeration control in the DSM method. Part one, Sci. Tech. Inf. Process., 2014, vol. 41, no. 6, pp. 335–347. https://doi.org/10.3103/S0147688214060082CrossRef

15.

Zabezhailo, M.I., Some capabilities of enumeration control in the DSM method. Part two, Sci. Tech. Inf. Process., 2014, vol. 41, no. 6, pp. 348–361. https://doi.org/10.3103/S0147688214060094CrossRef

Titel: On the Reliability of Medical Diagnosis Based on Empirical Data
verfasst von: M. I. Zabezhailo
Y. Y. Trunin
Publikationsdatum: 01.12.2021
Verlag: Pleiades Publishing
Erschienen in: Scientific and Technical Information Processing / Ausgabe 5/2021
Print ISSN: 0147-6882
Elektronische ISSN: 1934-8118
DOI: https://doi.org/10.3103/S0147688221050142

Springer Professional

Abstract

Bitte loggen Sie sich ein, um Zugang zu Ihrer Lizenz zu erhalten.

Sie haben noch keine Lizenz? Dann Informieren Sie sich jetzt über unsere Produkte:

Springer Professional "Wirtschaft+Technik"

Springer Professional "Wirtschaft"

Springer Professional "Technik"

Weitere Artikel der Ausgabe 5/2021

The Edgeworth–Pareto Principle in the Case of a Type-2 Fuzzy Preference Relation

Comparative Analysis of Inference Methods Based on the Fuzzy Truth Value for MISO-Structure Systems

Fuzzy Semantic Networks as a Knowledge Representation Model of Autonomous Intelligent Systems

“A Year Ago”: On Normalization of One Type of Temporal Expression

Decision Support Based on Human–Computer Collective Intelligence: Analysis of Methodologies and Ontology Model

Mental Actions and Mental Objects in the Space of Science Discourse

Premium Partner