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Estimating the number of data clusters via the contrast statistic

Journal of Biomedical Science and Engineering 2012年第2期5卷 95-99页

作者： yuriy lyakh Vitaliy Gurianov Oleg Gorshkov yuriy Vihovanets Department of Medical Biophysics Medical Informatics and Biostatistics National Medical University Donetsk Ukraine

A new method (the Contrast statistic) for estimating the number of clusters in a set of data is proposed. The technique uses the output of self-organising map clustering algorithm, comparing the change in dependency of “Contrast” value upon clusters number to that expected under a uniform distribution. A simulation study shows that the Contrast statistic can be used successfully either, when variables describing the object in a multi-dimensional space are independent (ideal objects) or dependent (real biological objects).

关键词： SOM Neural Network Clustering Gap Statistic Silhouette Statistic

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Forecasting of Survival Rate in Patients with the Early Stage of Non Small Cell Lung Cancer

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Journal of Cancer Therapy 2013年第10期4卷 1472-1477页

作者： Oleksey P. Kolesnik Anatoliy I. Shevchenko yuriy E. lyakh Vitaliy G. Gurianov Department of Medical Biophysics Medical Informatics and Biostatistics M. Gorky Donetsk National Medical University Donetsk Ukraine Department of Oncology Zaporizhzhya State Medical University Zaporizhzhya Ukraine

Lung cancer is the most common cause of death from oncological diseases all over the world. Primary treatment of patients with the early stage of non-small cell lung cancer is a surgery. However, after surgery 30% - 85% of patients undergo disease progression. In order to improve the results of treatment of patients with non-small cell lung cancer it is necessary to separate a group of patients with dismal prognosis for whom adjuvant chemotherapy will permit improving the survival rate. The aim of our research was to create a forecasting model with a view to detect the patients with the early stage of non-small cell lung cancer and dismal prognosis. Our research covered 254 patients with the early stage of non-small cell lung cancer who underwent a cure from June 2008 till December 2012 in the department of thoracic surgery of Zaporizhzhia Regional Clinical Oncologic Dispensary. In order to identify the factors connected with the risks of low survival rate of patients with the early stage of non-small cell lung cancer after curative treatment (surgical treatment, adjuvant chemotherapy), a method of design of neural network models of classification was used. 39 factors were taken for input characteristics. During investigation two forecasting models were built. As follows from the analysis of first forecasting model with the increase of the patient’s BMI, the risk of low patient survival rate statistically and significantly (p = 0.03) decreases, OR = 0.89 (95% CI 0.80 - 0.99) for each kg/m2 index value. The risk of low patient survival rate also decreases (p = 0.02) if he has a squamous cell carcinoma, OR = 0.36 (95% CI 0.15 - 0.88) compared with other histological forms of tumor. The connection between the risk of low patient survival rate and the volume of surgical intervention was discovered (p = 0.01), OR = 3.19 (95% CI 1.29 - 7.86) for patients who underwent a pulmonectomy compared with patients who underwent an upper bilobectomy. As follows from the analysis of

关键词： Forecasting Model Survival Rate Non-Small Cell Lung Cancer

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Usage of Cox-Regression Model for Forecasting of Survival Rate in Patients with the Early Stage of Non-Small Cell Lung Cancer

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Advances in Lung Cancer 2014年第1期3卷 26-33页

作者： Oleksey P. Kolesnik Anatoliy I. Shevchenko yuriy E. lyakh Vitaliy G. Gurianov Pavel A. Alyoshechkin Department of Medical Biophysics Medical Informatics and Biostatistics M. Gorky Donetsk National Medical University Donetsk Ukraine Department of Oncology Zaporizhzhya State Medical University Zaporizhzhya Ukraine

In the past decades a lot of investigations were focused on searching for more accurate markers of lung cancer progression. Researchers indicate that molecular markers may be useful in forecasting of treatment outcome and overall survival rate in patients with non-small cell lung cancer. The aim of our research was to create a forecasting model in order to identify patients with stage I-II of non-small cell lung cancer and dismal prognosis. Our research covered 254 patients with the early stage of non-small cell lung cancer who underwent a cure from June 2008 till December2012 inthe Department of Thoracic Surgery of Zaporizhzhia Regional Clinical Oncologic Dispensary. Surgery was performed for all patients. Adjuvant chemotherapy was performed for 101 patients. In order to carry out multivariate Cox-regression analysis, STATISTICA 6.0 (StatSoft Inc.) program was used. The most significant from 39 variables were selected (tumor size, histological form of tumor, volume of surgical intervention, volume of conducted lymph node dissection, Ki-67 expression, EGFR expression, E-cadherin expression). We propose the computer system which can forecast survival rate in patients with the early stage of non-small cell lung cancer.

关键词： Forecasting Model Survival Rate Non-Small Cell Lung Cancer

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