Blood Transfusion Dataset

Dataset Information:

• Total Records: 748 blood donors
• Purpose: To analyze donor behavior and predict future blood donations
• Data Collection: Donors were selected randomly from the center’s database, focusing on those who have interacted with the mobile blood donation bus that visits a local university approximately every three months.

Attributes:

1. Recency (R): Number of months since the donor’s most recent blood donation.
2. Frequency (F): Total number of times the donor has donated blood.
3. Monetary (M): Total volume of blood donated in cubic centimeters (c.c.).
4. Time (T): Number of months since the donor’s first blood donation.
5. Donation in March 2007: Binary indicator (1 if the donor gave blood in March 2007, 0 otherwise).

Statistical Summary:

• Recency:
  • Minimum: 0.03 months
  • Maximum: 74.4 months
  • Mean: 9.74 months
  • Standard Deviation: 8.07 months
• Frequency:
  • Minimum: 1 donation
  • Maximum: 50 donations
  • Mean: 5.51 donations
  • Standard Deviation: 5.84 donations
• Monetary:
  • Minimum: 250 c.c.
  • Maximum: 12,500 c.c.
  • Mean: 1,378.68 c.c.
  • Standard Deviation: 1,459.83 c.c.

Dataset Split:

• Training Set: 500 donors (used to build predictive models)
• Testing Set: 248 donors (used to evaluate model performance)

Potential Applications:

• Predictive Modeling: Develop machine learning models to forecast donor behavior, improving the efficiency of blood collection campaigns.
• Donor Retention Strategies: Identify factors that contribute to donor loyalty and design targeted retention programs.
• Resource Allocation: Optimize the deployment of mobile donation units based on predicted donor turnout.

Ethical Considerations:

• Data Privacy: Ensure all personal and sensitive information is anonymized to protect donor identities.
• Consent: Confirm that donors have provided consent for their data to be used in research and analysis.
• Compliance: Adhere to local and international regulations regarding data protection and ethical research practices.

Conclusion:

The enriched Blood Transfusion Service Center Dataset offers a comprehensive foundation for analyzing and predicting blood donation behaviors. By integrating additional variables and adhering to ethical standards, organizations can gain valuable insights to enhance donor engagement, streamline operations, and ultimately contribute to a more reliable blood supply for those in need.