Data Mining in Healthcare. What is Data Mining introduction

"Data-Mining-in-Healthcare. “ provides a comprehensive overview of how data mining is transforming the healthcare sector by unlocking valuable insights from complex medical data.
The presentation introduces data mining as the process of extracting meaningful knowledge from large datasets using statistical, machine learning, and database techniques, emphasizing its role in solving business problems, improving processes, and predicting outcomes within healthcare.
data mining is revolutionizing healthcare by enabling proactive, predictive, and personalized care, with ongoing innovations and challenges related to privacy and data integration.
This presentation offers a structured exploration of data mining’s impact, methodologies, and significance in modern healthcare.

1. Data Mining in Healthcare Unlocking the Power of Medical Data Presented by: Ajay Chaure BSc (optional CS) TY Date: 30/07/2025 Deogiri College Chhatrapati Sambhajinagar

2. Table of Content Introduction to Data Mining Why Healthcare Needs Data Mining Benefits of data mining in healthcare How does data mining work in healthcare ? Data Mining Techniques in Healthcare Applications in Real Life Challenges in Healthcare Data Mining

3. Table of Content The future of data mining in healthcare Conclusion

4. Introduction to Data Mining Data mining is the process of extracting useful insights and knowledge from large datasets. It involves applying techniques from statistics, machine learning and database systems to find hidden patterns, relationships and trends. These insights can be used to solve business problems, improve processes and predict future outcomes. 

5. Why Healthcare Needs Data Mining Data mining is crucial in healthcare because it enables the analysis of massive datasets to uncover hidden patterns and insights that can improve patient care, optimize resource allocation, and reduce costs. It facilitates evidence-based decision making, predictive analytics, and personalized medicine, ultimately leading to more efficient, effective, and proactive healthcare delivery

6. Benefits of data mining in healthcare Enhanced clinical decision-making Increased diagnosis accuracy Improved treatment efficiency Avoiding harmful drug and food interactions Enabling predictive analysis Better customer relationships

7. How does data mining work in healthcare? When all the components are in place, the process of mining data will go through the following stages: Acquisition/selection.  During this stage, a target set is created with original data. Preprocessing.  Data is formatted, and its quality is standardized. Mining.  The actual step of detecting patterns and knowledge. Interpretation.  Extracting insights from the patterns mined.

8. Techniques used in data mining Classification Clustering Association Outlier detection Prediction

9. Applications in Real Life Disease Prediction & Diagnosis Clinical Decision Support Systems (CDSS) Hospital Resource Management Genomic Data Analysis Public Health Monitoring

10. Challenges in Healthcare Data Mining Data privacy and patient consent Incomplete or inconsistent data Integration across systems Ethical concerns in decision-making

11. The future of data mining in healthcare More efficient treatment of rare diseases Higher survival rates for cancer patients Drastic improvements in quality of care for patients, including underprivileged groups Pre-emptive measures against infectious diseases at the national level Real-time analytics from wearables/IoT

12. Conclusion Data mining is transforming healthcare Enables proactive, predictive, and personalized care Ethical and secure usage is crucial for long-term impact Despite challenges like data integration, resource limitations, and privacy issues As the field progresses, data mining projects in healthcare will help foster innovation and enhance the quality of healthcare services.

13. Thank You ! Do you have any questions ? Created by:- Ajay Chaure