Update README.md

README.md

-# Title
+# [Title]
 
 ## Introduction
+This GitLab repository contains the main material used in the paper [title] by [authors]. 
 
+The study examines patients undergoing treatment for alcohol disorders, utilizing machine learning techniques to predict clinical success or withdrawal. The main goal is to employ explainability tools to assess the impact of individual versus social factors on treatment outcomes. Additionally, the research explores whether the significance of these factors changed during the pandemic by comparing pre-pandemic and post-pandemic patient groups.
+
+[Impact?]
+
+## About the Dataset
+[Origin, Characteristics]
+
+The dataset has not been provided since the authors do not have permission for its sharing from the data providers.
 
 ## Dealing with Class Imbalance
 One of the primary challenges we encountered was a significant class imbalance, with a higher number of patients withdrawing from treatment compared to those staying.
@@ -14,6 +23,8 @@ To address this issue, we implemented four different training approaches or pipe
 
 These approaches resulted in multiple training datasets. However, to ensure a fair comparison of the models' performance across different pipelines, we utilized a common test dataset for evaluation, irrespective of the training approach followed.
 
+## Methodology Overview
+
 ## Repository
 This repository is organized as follows:
 * [EDA](./EDA): 
@@ -37,8 +48,6 @@ This repository is organized as follows:
     * [shap_plots.py](./explainability/shap_plots.py): Generating SHAP summary plots for the SHAP and SHAP interaction values computed. Comparing major differences between pre- and post-pandemic groups.
     * [output](./explainability/output): SHAP and SHAP interaction summary plots.
 
-## Data
-
-The dataset has not been provided since the authors do not have permission for its sharing from the data providers.
-
+## Contact
 For any inquiry you can contact:
+[Contact Info]