references
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24
report.tex
24
report.tex
@@ -105,7 +105,7 @@
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\begin{tabular}{lrrl}
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\!\!\!Student, & \hspace{2cm} & & \\
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\!\!\!group 5130201/20102 & \hspace{2cm} & \underline{\hspace{3cm}} &Tishenko А. А. \\\\
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\!\!\!Supervisor & \hspace{2cm} & \underline{\hspace{3cm}} & Motorin D. E. \\\\
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\!\!\!Supervisor, Ph. D. & \hspace{2cm} & \underline{\hspace{3cm}} & Motorin D. E. \\\\
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&&\hspace{4cm}
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\end{tabular}
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\begin{flushright}
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@@ -134,9 +134,23 @@
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% \subsection{Первый подраздел}
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% Текст первого подраздела
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% \section*{Заключение}
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% \addcontentsline{toc}{section}{Заключение}
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% \section*{Conclusion}
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% \addcontentsline{toc}{section}{Conclusion}
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% Conclusion text
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% Текст заключения
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\newpage
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% \section*{Literature}
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% \addcontentsline{toc}{section}{Literature}
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\vspace{-1.5cm}
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\begin{thebibliography}{0}
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\bibitem{paclitaxel}
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Lu Xin, Wen Xiao, Huanzhi Zhang, Yakun Liu, Xiaoping Li, Pietro Ferraro, Feng Pan, Classification of paclitaxel-resistant ovarian cancer cells using holographic flow cytometry through interpretable machine learning, 2024.
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\bibitem{heterogeneity}
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Qiuli Zhu, Hua Dai, Feng Qiu, Weiming Lou, Xin Wang, Libin Deng, Chao Shi, Heterogeneity of computational pathomic signature predicts drug resistance and intra-tumor heterogeneity of ovarian cancer, 2024.
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\bibitem{mitochondria}
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Ziyu Liu, Zahra Zeinalzadeh, Tao Huang, Yingying Han, Lushan Peng, Dan Wang, Zongjiang Zhou, DIABATE Ousmane, Junpu Wang, Mitochondria-related chemoradiotherapy resistance genes-based machine learning model associated with immune cell infiltration on the prognosis of esophageal cancer and its value in pan-cancer, 2024.
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\bibitem{sers}
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Jun Zhang, Youliang Weng, Yi Liu, Nan Wang, Shangyuan Feng, Sufang Qiu, Duo Lin, Molecular separation-assisted label-free SERS combined with machine learning for nasopharyngeal cancer screening and radiotherapy resistance prediction, 2024.
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\end{thebibliography}
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\end{document}
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