Liver Diseases Prediction analysis in india

India liver disease a case study

1. Liver Diseases Prediction using Machine Learning 9568 Glison Pereira 9636 Ricky Rodrigues 9647 Joel Varghese

2. Table of contents 01 04 02 05 03 Abstact Motivation Problem statement Aims Objectives 06 Methodology 07 Requirements 08 Litreature Survey 09 Conclusion

3. Abstract Liver disease is a major public health problem, affecting millions of people worldwide. What makes it even more deadly is the lack symptoms. Early diagnosis and treatment which are essential for treatment of the disease does not occur due to the nature of diseases which causes serious complications, such as liver failure. However, traditional methods of diagnosing liver disease can be expensive and time-consuming. As a solution to this problem we propose to developing a system using various machine learning algorithms which can help to simplify the process and may also able to save lives.

4. Motivation One of the main reasons for choosing this topic is that liver diseases if diagnoised early can be easily treated. But liver as a peculiar organ as a ability to heal its self this does not allow the early onset of symtomns required for diagnoising the patient this also causes at times to be unaware regarding the problem itself until its too late Other reasons for selecting include: To decrease the load on the doctors To eliminate the scope of human error during diagnosis

5. Problem Statement Design a systems which can make use various machine learning algorithms to accurately classify and predict the onset liver diseases and complications arising out of it

6. The project aims to develop a liver disease prediction system using machine learning. The system will collect data from patients, such as their medical history, blood test results, and imaging scans. The system will then use machine learning algorithms to analyze this data and identify patients who are at risk of developing liver disease. Aims

7. Objectives The objectives of this project are as follows Collect data from patients, such as their medical history, blood test results, and imaging scans. Clean and prepare the data for machine learning. Select and train machine learning algorithms. Evaluate the performance of the system. Deploy the system to a production environment.

8. Methdology Data Collection/Dataset Selection Preprocessing Feature Selection Selecting Machine learning algos Model Training Testing Deploying in society Future improvements 01 02 03 04 05 06 08 07

9. Requirements Software Python and Python libraries such as sklearn and imblearn Dataset(Indian Liver Patients Dataset ) Hardware CPU: A modern CPU with at least 2 cores and 4 GB of RAM. GPU: A GPU is not required, but it can improve the performance of the system. Storage: The system will require at least 10 GB of storage space. Operating system: The system can be run on any operating system that supports Python.

10. Literature Survey [1] Liver Disease Prediction Using Machine Learning Algorithms Authors: R. Kalaiselvi; K. Meena; V. Vanitha This paper appears in: International Conference on Advancements in Electrical, Electronics, Communication, Computing and Automation (ICAECA), Coimbatore, India, 2021. [2] Evaluation based Approaches for Liver Disease Prediction using Machine Learning Algorithms Authors: C. Geetha; AR. Arunachalam This paper appears in: International Conference on Computer Communication and Informatics (ICCCI), Coimbatore, India, 2021. [3] K. Gupta, N. Jiwani, N. Afreen, and D. D, “Liver disease prediction using machine learning classification techniques,” 2022 IEEE 11th International Conference on Communication Systems and Network Technologies (CSNT), Apr. 2022. doi:10.1109/csnt54456.2022.9787574 [4] N. Tanwar and K. F. Rahman, “Machine learning in liver disease diagnosis: Current progress and future opportunities,” IOP Conference Series: Materials Science and Engineering, vol. 1022, no. 1, p. 012029, 2021. doi:10.1088/1757-899x/1022/1/012029

11. Conclusion To Conclude w e selected the project so that we could serve the society with the technical skills we developed.We would also be very pleased if ths project could be helpful even if it’s a small quantity of people

12. Thank You