Symptom Based Disease Prediction Using Machine learning

Advances in machine learning techniques have paved the way for innovative applications in healthcare, including symptom-based early disease diagnosis.This study presents a new system that uses machine learning algorithms to predict potential diseases based on symptoms entered by a user.To ensure the quality of the data, extensive material containing various symptoms and similar diseases was collected and pre-processed.Feature engineering techniques were used to extract relevant information from the dataset, facilitating efficient model training.Based on the processed data, a random forest classifier was selected and trained to classify symptoms into possible disease categories.To improve user interaction and accessibility, a graphical user interface (GUI) was developed using Tkinter to allow users to seamlessly enter their symptoms.Integration of a trained machine learning model in Tkinter's GUI enables real-time prediction of likely diseases, which helps in timely consultation with a doctor and initiation of treatment..