Abstract: Using Machine learning, our project proposes disease prediction system. For small problems, the users have to go personally to the hospital for check-up which is more time consuming. Also handling the telephonic calls for appointments is quite hectic. Such a problem can be solved by using disease prediction application by giving proper guidance regarding healthy living. Over the past decade, the use of the specific disease prediction tools along with the concerning health has been increased due to a variety of diseases and less doctor-patient ratio. Thus, in this system, we are concentrating on providing immediate and accurate disease prediction to the users about the symptoms they enter along with the severity of disease predicted. Best suitable algorithm and doctor consultation will be given in this project. For prediction of diseases, different machine learning algorithms are used to ensure quick and accurate predictions. In one channel, the symptoms entered will be crosschecked with the database. Further, it will be preserved in the database if the symptom is new which its primary work is and the other channel will provide severity of disease predicted. A web/android application is deployed for user for easy portability, configuring and being able to access remotely where doctors cannot reach easily. Normally users are not aware about all the treatment regarding the particular disease, this project also looks forward to providing medicine and drug consultation of disease predicted. Therefore, this arrangement helps in easier health management.
Keywords: Machine Learning, KNN algorithm, SVM, Decision Tree Algorithm, Naïve Bayes Algorithm, Django, Python, etc
| DOI: 10.17148/IJARCCE.2019.81210