From 6f616e25f18ecc8a17ab4928dfe89dc70f9a7463 Mon Sep 17 00:00:00 2001
From: Arity-T <tish.mainmail@gmail.com>
Date: Mon, 25 Nov 2024 12:24:58 +0300
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---
 report.tex | 9 +++++++++
 1 file changed, 9 insertions(+)

diff --git a/report.tex b/report.tex
index be2a442..3f49e93 100644
--- a/report.tex
+++ b/report.tex
@@ -15,6 +15,7 @@
 \usepackage{graphicx}
 
 \usepackage{pdfpages}
+\usepackage{tikz}
 
 \usepackage{array}
 \usepackage{multirow}
@@ -188,6 +189,14 @@
     
     In \cite{kras}, authors firstly applied machine learning algorithms to extract most important features and created seven feature lists, after that they applied four classification algorithms. Their best result was achieved with CATBoost feature list and support vector machine as classification algorithms (accuracy of 93.1\%). Also after analysing recieved feature lists authors were able to identify top genes associated with tumor progression and drug resistance (H2AFZ, CKS1B, TUBA1B, RRM2, BIRC5).
 
+    \addtocounter{table}{1}
+    \includepdf[pages={1}, fitpaper, pagecommand={
+    \thispagestyle{empty}
+        \begin{tikzpicture}[remember picture, overlay]
+            \node at (current page.north) [anchor=north, yshift=-30pt] {Table 1. Methods used in research papers.};
+        \end{tikzpicture}
+    }]{methods_table/methods.pdf}
+
 
     \newpage
     \begin{table}[h!]