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Multiple Diseases Prediction Using Machine Learning

Authors:

Tejasvini Govinda Mahajan ¹, Tejaswini Sanjay Kadam², Tanushka Rajendra Patil ³_,

Yogeshwari Manoj Patil ⁴, Prof. Rashmi Bahirune ⁵

UG Student, Dept. of Computer Engineering, KCE’s College of Engineering and Management, Jalgaon, India^1-

Assistant Professor, Dept. Of Computer Engineering, KCE’s College of Engineering and Management, Jalgaon, India²

Abstract - The Multiple Diseases Prediction Using Machine Learning project intends to become that intelligent and efficient system that will predict the chances of getting various diseases from the health data shared by the user with the algorithm. Multiple models like Decision Trees, Random Forests, Support Vector Machines, and Neural Networks are trained on extremely large medical datasets containing symptoms, demographics, and clinical measurements. After preprocessing the data to deal with missing values, normalize the inputs, and carry out feature selection, the systems then learn to associate different patterns and correlations with various diseases. With the considered diseases, the system makes one of its predictions for diabetes, heart diseases, kidney disorders, and liver disorders with great accuracy. This specifically brings about the early detection and diagnosis, so that physicians can further decide based on this, thereby elevating the standard of patient care. With its simple-to-use interface, an individual can enter his/her health parameters and obtain instant predictions, bringing healthcare within reach, making it much more proactive and personalized through machine learning.

Key Words: Machine Learning, Multiple Disease Prediction, Healthcare Analytics, Early Diagnosis, Artificial Intelligence in Healthcare, Prediction Modeling, Classification Algorithms, Features selection, Decision support system.