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+# Using Machine Learning to Analysis of Blood Donation
+## Which features impact high blood donation? 
+![Blood_donation_img](https://github.com/Hyunjin-Austin/Blood-Donation-Analysis/blob/b11e44c3af60536b0b2ee32221b31fb819231d94/icons8-blood-donation-78.png)
+* Blood donation is the only method to secure accessibility of blood products for patients in need of transfusion and accessibility is solely dependent on voluntary non-remunerated blood donors.
+* Many countries' health authorities and blood centers are striving to have sufficient blood donations to secure a stable blood supply in the country or region.
+* In this case study, we aimed to find features that could help improve blood donation performance in South Korea.
+* The objective of this case study is as follows:
+  * Analyze the trend of blood donations in South Korea since 2005 
+  * Identify which features have a significant impact on high blood donation
+  * Recommendations for blood centers to increase blood donation
+* To identify important features, we built various machine-learning models from simple Logistic Regression to the XGBoosting Classifier model.
+* Platforms used for this project
+  * Python: Pandas, Scikit-learn, Xgboost
+  * Visualization: Tableau, Seaborn
+## Project Outline
+1. Plan Stage: Data collection, Data dictionary, Pre-processing & Feature engineering
+2. Analyze Stage: Exploratory Data Analysis (EDA)
+3. Construct Stage: Prepare, Construct, and train & test models 
+4. Execute Stage: Interpret model performance, conclusion (recommendation)
+## Note for this project
+  * The data used for this project is entirely from public open data, extracted from KOSIS (Korean Statistical Information Service). No internal data was included.
+  * This project was worked with <ins>**Yoojin (Audrey) Jung**</ins>, a data analyst, with a master's degree from the University of Illinois Urbana-Champaign (UIUC).
+    * **(Skills)** Data Analytics, Visualization (Tableau), SQL, R, Python
+    * **(Contributions to this project)** EDA (Processing & Visualization), Tableau, model design (logistic regression, decision tree)
+    * **(LinkedIn Profile)** https://www.linkedin.com/in/yoojin-jung/
+## Citation
+If you use (or refer to) this project in your research (study), please cite it as follows:
+  * Author: Hyunjin and Yoojin
+  * Title: Using Machine Learning to Analysis of Blood Donation
+  * Year: 2024
+  * Publisher: Hyunjin-Austin
+  * Journal: Blood-Donation-Analysis
+  * How published: https://github.com/Hyunjin-Austin/Blood-Donation-Analysis/ <br><br>
+  
+Thank you for citing our work!