Recommend Medication for Diabetic Patients using Data Science
There are nearly 370+ million individuals everywhere have diabetes. Diabetic medication management is usually difficult. Patients take hormone dose one hour before lunch or dinner or breakfast based on Dr's prescription. However the real world state of affairs the hormone intake may be modified based on the glucose level, calorie intake on a particular day. Based on Calorie intake and glucose level of the general public further as generated dataset advocate hormone dose which is able to facilitate patients to avoid over/under dose. This project uses big data Pipeline and predicts medication for diabetic patients supported their glucose level. It uses Data science models for the recommendation. This project can improve the approach to life of the diabetic patients by taking correct medication.
Keywords - Diabetes; Data Science; Predicting Medication; Apache Kafka and Spark; Spark Mllib.