Paper Title : Disease Prediction using Machine Learning based on User Symptoms

ISSN : 2394-2231
Year of Publication : 2021

10.29126/23942231/IJCT-v8i2p47

Authors: Ananya Ubarhande, Kalpit Vyas, Sahil Sapar, Rutuja Jadhav , Prof. Rupali Waghmode

         



MLA Style: Ananya Ubarhande, Kalpit Vyas, Sahil Sapar, Rutuja Jadhav , Prof. Rupali Waghmode " Disease Prediction using Machine Learning based on User Symptoms " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

APA Style: Ananya Ubarhande, Kalpit Vyas, Sahil Sapar, Rutuja Jadhav , Prof. Rupali Waghmode " Disease Prediction using Machine Learning based on User Symptoms " Volume 8 - Issue 2 March-April , 2021 International Journal of Computer Techniques (IJCT) ,ISSN:2394-2231 , www.ijctjournal.org

Abstract
Nowadays, we live in a world where people suffer from various diseases due to conditions like environmental changes and various dangerous experiments like Covid19. So the prediction of disease at an earlier stage became the most important task and correct prediction of disease is the most challenging task. Here we proposed a system that can identify diseases based on symptoms. There are many applications like online consultation with a doctor but there is less number of application that predict diseases. There are systems where only one disease can be predicted by using the symptoms but in our system, we can predict forty-one common diseases. For prediction purpose, we required some symptom’s dataset. With the help of the disease symptom dataset from the Kaggle platform, we find a huge amount of information to process in this system for accurate prediction. For the prediction purpose, we use three algorithms of machine learning which are Naïve Bayes, Random Forest, and Decision Trees. After prediction of disease, the system will provide detail information about diseases and provide the option to book an appointment for a required doctor which is also a part of our system where patient selects doctor for his/her treatment and book their appointments accordingly.

Reference
1. “Disease Prediction using Machine Learning Algorithms” Sneha Grampurohit, Chetan Sagarnal 2020 International Conference for Emerging Technology (INCET) Belgaum, India. Jun 5-7, 2020 2. “Symptom Based Health Prediction using Data Mining” Vijaya Shetty S, Karthik G A, M Ashwin Proceedings of the Fourth International Conference on Communication and Electronics Systems (ICCES 2019) IEEE Conference Record # 45898; IEEE Xplore ISBN: 978-1-7281-1261-9 3. Y.Deepthi,K. Pavan Kalyan,Mukul Vy as,K. Radhika,D. Kishore Babu, N. V. Krishna Rao “Disease Prediction Using Machine Learning”. 4. Shadab Adam et.al “Prediction system for Heart Disease using Naïve Bayes”, International Journal of advanced Computer and Mathematical Sciences, ISSN 2230- 9624, Vol 3,Issue 3,2012,pp 290- 294[Accepted12/06/2012] 5. Sohail M.N., Jiadong R., Uba M.M., Irshad M. (2019) A Comprehensive Looks at Data Mining Techniques Contributing to Medical Data Growth: A Survey of Researcher Reviews. In: Patnaik S., Jain V. (eds) Recent Developments in Intelligent Computing, Communication and Devices. Advances in Intelligent Systems and Computing, vol 752. Springer, Singapore

Keywords
————— Machine Learning, Diseases, Decision Tree classifier, Random forest classifier, Naive Bayes classifier, Symptoms