The document discusses disease prediction using machine learning, highlighting its potential to predict various diseases based on patient data. It outlines the advantages, such as early detection and improved lifestyle, and disadvantages, including accuracy issues and dependence on large datasets. The conclusion emphasizes the growing technology's promise in predicting deadly diseases, though acknowledging the need for further improvements.

1. DISEASE PREDICTION
USING ML
Rakesh Kumar Lenka
1901206101
CSE

2. Disease Prediction using Machine Learning is the system that
is used to predict the diseases from the data which are given
by the patients or any user.
INTRODUCTION
2

3. CONTENT
3
 Introduction
 Data Flow Diagram
 Why Diabetes
 Live Explanation
 Future Scope
 Advantages
 Disadvantages
 Conclusion
 References

4. DATAFLOW DIAGRAM
4
DATA FLOW DIAGRAM

5. WHY DIABETES
*Source Internet
5
Prediction Using ML
• Heart Disease
• Lungs Cancer
• Liver Disease
• Stroke
• Breast Cancer
• Kidney Disease

6. FUTURE SCOPE
6
When ever a person do his/her health
checkup the machine can predict the
disease in which he/she can be affected
in the future.
Early Prediction
The accuracy of the ML Model can be
increased and it can become very
efficient that we can trust the result.
High Accuracy
Rate
Electronics health records consist of
entire medical and health data in a single
system to ensure data availability and
accessibility.
Electronic Health
Record

7. ADVANTAGES OF DISEASE PREDICTION
7
• If we can predict a disease before hand then
we can take necessary steps to avoid the
disease and hence can save the lives of our
dear one.
Can Save Thousands Of Lives
• Government can take mass measures to
fight against the diseases that are going to
prevail
Govt. can get benefit
• By predicting diseases we can actually
improve people’s lifestyle up to a great
extend.
Can improve life style

8. DISADVANTAGES OF DISEASE PREDICTION
8
• As no model is 100% accurate so we can’t
be very clear about the results.
Accuracy Issues
• Without huge data set we can’t get accurate
results sometimes the model can predict
wrong disease as well.
Requires Big Amount Of Data
• If the input dataset is wrong then the model
will predict wrong disease accordingly.
Wrong DataSet Issue

9. CONCLUSION
9
 Disease prediction is a growing technology
 It can predict deadly disease and save lives
 But still a lot of improvements can be done in this filed
 Like diabetes we can also predict other diseases using this technique

10. 10
REFERENCES
 https://ieeexplore.ieee.org/
 https://www.researchgate.net/
 https://www.sciencedirect.com/
 https://www.python.org/
 https://jupyter.org/
 https://www.pythonsoft.org/
 https://www.slideshare.net/

11. THANK
YOU
Rakesh Kumar Lenka
6th Sem,CSE