Use of the Computer Statistics in Oncology

Year : 2023 | Volume : 12 | Issue : 01 | Page : 01-21

    M. Shoikhedbrod


Currently, the use of computer statistics and computer statistical modeling in oncology for obtaining an accurate diagnosis, determination of the choice of treatment method and its correction in the process of ongoing treatment, prediction of the outcome of the disease, and evaluation of the effectiveness of the chosen treatment tactics is a decisive factor. The use of computer statistics, based on an adapted scientific and statistical package of the SSP in oncology, which is the basis for the use
of computer statistical modeling of oncological processes, plays an important role in the effective treatment of cancer patients in clinical practice, since it permits, based on the creation of a computer medical and statistical to actively engage in the care of individuals undergoing cancer treatment, modify this statement. Effective
articipation in the treatment of cancer patients occurs due to the implementation of the tactics of individual planning of the examination of the patient, individualized
prognosis, which determine the possibility of an individual approach to the observation and postoperative treatment of the patient according to the constructed medical-statistical model. This paper presents the results of computer-statistical processing of information from cancer patients, using the SSP package of scientific and
statistical programs, which became the basis for the development of a computer statistical optimal interpolation model for accurately predicting of the timing of the appearance of metastases after surgery and of evaluating of the effectiveness of treatment of malignant neoplasms.

Keywords: Computer statistics, computer statistical modeling, computer optimal interpolation, estimation of malignant new formations treatment efficiency, precise prognosis of metastases appearance timing

[This article belongs to Research & Reviews : Journal of Statistics(rrjs)]

How to cite this article: M. Shoikhedbrod Use of the Computer Statistics in Oncology rrjs 2023; 12:01-21
How to cite this URL: M. Shoikhedbrod Use of the Computer Statistics in Oncology rrjs 2023 {cited 2023 Jun 17};12:01-21. Available from:


  1. IBM Corporation. System/360 Scientific Subroutine Package (360A-CM-03X) Version III.(1968).
  2. Egoshin VL, Ivanov SV, Savvina NV, Kapanova GZ, Grjibovski AM. Descriptive statistics using R. Ekolo Cheloveka/Hum Ecol. 2018; (9): 55–64.
  3. Bewick V, Cheek L, Ball J. Statistics review 7: Correlation and regression. Crit Care. 2003 Dec; 7: 1–9
  4. Malinowski, Edmund R, Darryl G. Howery. Factor analysis in chemistry. New York: Wiley, 1980 Vol.3
  5. Kline P. An easy guide to factor analysis, Routledge, 2014.
  6. Shoikhedbrod MP. The use of developed computer medical process manager, “Medical Commander” for Application in Medical Practice, Int J Softw Comput Test. 2020; 6(2): 12–27.
  7. Shoikhedbrod MP. Computer modeling and the new technologies in oncology. 2017; 1–116.
  8. Shoikhedbrod MP. Computer modeling in physics and medicine, Lambert Academic publishing, Toronto, 2018
  9. Shoikhedbrod DM. Programming of the Computer Manager of Medical Processes “Medic Commander” Software Application on Computer Language Turbo C. J Comput Sci Eng Softw Test. 2022; 8(1): 1–34. (e-ISSN: 2581-6969). Available from:
  10. Enderling H, AJ Chaplain M. Mathematical modeling of tumor growth and treatment. Curr Pharma Design. 2014 Sep 1; 20(30): 4934–40.
  11. Shoikhedbrod M. Principles of Interpolating Prognostication in Oncology. Research & Reviews: J Oncol Hematol. 2020; 9(2): 39–51. Available from:
  12. Akhmedov BP, Akhmedova Sh. B. The results of the application of special mathematical methods of study on the computer in the study of prognostication and modeling of the processes of the generalization of malignant new formations. Tashkent. 2002.

Regular Issue Subscription Article
Volume 12
Issue 01
Received May 28, 2023
Accepted June 8, 2023
Published June 17, 2023