The application of data mining is visible in fields like commerce, e-business, and trade. The medical fields are rich in information but the knowledge is still weak. Data wealth is high in the medical field. But there is a lack of analytic tools to analyze trends in data. Here we implement a hospital management software in order to computerize the front office workflow and it implements Predictive models for the diseases using machine learning algorithms. The front office management deals with the collection of patient information and diagnosis details etc. Traditionally all these works were done manually and using this software we can digitalize the entire operations. We are implementing this hospital management software and predictive models in Ayurveda. As the initial step, we are implementing a predictive model for Arthritis, by analyzing Rheumatoid Factor (RF), age and symptoms of the patient. There are five types of arthritis Gout, Rheumatoid arthritis, Osteoarthritis, Psoriatic arthritis, and Juvenile arthritis. The age, RF value, and age determine the type of arthritis the person possesses. Rheumatoid factor is an antibody that can be detected in the blood of a person who has arthritis. We use six machine learning algorithms here. They are SVM, CART, Linear Regression, KNN, Naïve Bayes, Linear Discriminant analysis.
SVM, CART, KNN, LDA, Naïve bayes, machine learning, arthritis prediction, rheumatoid factor
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