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CLASSIFICATION OF LUNG CANCER DISEASES BY SUPPORT VECTOR METHOD

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SCIENCE AND INNOVATIVE DEVELOPMENT

SCIENCE AND INNOVATIVE DEVELOPMENT

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ARTICLE ANNOTATION

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Among all cancers, lung cancer accounts for the largest proportion of patients. The fact that the mortality rate of patients with this type of cancer makes 18% of the number of deaths from oncologic diseases, shows relevance of the research in this area. A clear evidence of this is the fact that in our country, statistics of lung cancer patients and those who die from its implications, is increasing every year. This paper reviews the issue of classifying the level of lung cancer in patients using the support vector method. The benchmark data obtained from kaggle.com was used as a training set. The main stages of the support vector method chosen as the research method are being closely described. Findings from classification of morbidity levels are being explained using tables and graphs. The study proves that the support vector method can serve as a positive solution for application in various fields including the medical practice. Moreover, it is being emphasized that the training set used in the study is worthy of applying in the real process.

AUTHORS

M.Xudayberdiyev

Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti, “Axborot texnologiyalarining dasturiy ta’minoti” kafedrasi

B.Achilov

Muhammad al-Xorazmiy nomidagi Toshkent axborot texnologiyalari universiteti, “Axborot texnologiyalarining dasturiy ta’minoti” kafedrasi

N.Alimqulov

Zahiriddin Muhammad Bobur nomidagi Andijon davlat universiteti

Tags

# qaror qabul qilish# decision# early detection# алгоритмы машинного обучения# метод опорных векторов# классификация рака лёгкого# раннее выявление# принятие решения# mashinali o‘qitish algoritmlari# tayanch vektorlar usuli# o‘pka saratonini tasniflash# erta aniqlash# machine learning algorithms# support vector method# lung cancer classification

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Article Identifiers

ROI:

https://eroi.uz/11.0094/A1024-0008

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