Using Naïve Bayes Algorithm to Estimate the Response to Drug in Lung Cancer Patients

Author(s): Baoling Guo, Qiuxiang Zheng*

Journal Name: Combinatorial Chemistry & High Throughput Screening
Accelerated Technologies for Biotechnology, Bioassays, Medicinal Chemistry and Natural Products Research

Volume 21 , Issue 10 , 2018

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Aim and Objective: Lung cancer is a highly heterogeneous cancer, due to the significant differences in molecular levels, resulting in different clinical manifestations of lung cancer patients there is a big difference. Including disease characterization, drug response, the risk of recurrence, survival, etc.

Method: Clinical patients with lung cancer do not have yet particularly effective treatment options, while patients with lung cancer resistance not only delayed the treatment cycle but also caused strong side effects. Therefore, if we can sum up the abnormalities of functional level from the molecular level, we can scientifically and effectively evaluate the patients' sensitivity to treatment and make the personalized treatment strategies to avoid the side effects caused by over-treatment and improve the prognosis.

Result & Conclusion: According to the different sensitivities of lung cancer patients to drug response, this study screened out genes that were significantly associated with drug resistance. The bayes model was used to assess patient resistance.

Keywords: Naïve bayes, lung cancer, drug sensitivity, functional deviation, drug resistance, treatment strategies.

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Article Details

Year: 2018
Published on: 26 February, 2019
Page: [734 - 748]
Pages: 15
DOI: 10.2174/1386207322666190125151624
Price: $65

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